Impact of Resolution on the Tropical Pacific Circulation in a Matrix of Coupled Models
NAO–ocean circulation interactions in a coupled general circulation model
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Transcript of NAO–ocean circulation interactions in a coupled general circulation model
NAO–ocean circulation interactions in a coupled generalcirculation model
A. Bellucci Æ S. Gualdi Æ E. Scoccimarro ÆA. Navarra
Received: 18 May 2007 / Accepted: 2 April 2008 / Published online: 18 April 2008
� Springer-Verlag 2008
Abstract The interplay between the North Atlantic
Oscillation (NAO) and the large scale ocean circulation is
inspected in a twentieth century simulation conducted with
a state-of-the-art coupled general circulation model. Sig-
nificant lead–lag covariance between oceanic and
tropospheric variables suggests that the system supports a
damped oscillatory mode involving an active ocean–
atmosphere coupling, with a typical NAO-like space
structure and a 5 years timescale, qualitatively consistent
with a mid-latitude delayed oscillator paradigm. The two
essential processes governing the oscillation are (1) a
negative feedback between ocean gyre circulation and the
high latitude SST meridional gradient and (2) a positive
feedback between SST and the NAO. The atmospheric
NAO pattern appears to have a weaker projection on the
ocean meridional overturning, compared to the gyre cir-
culation, which leads to a secondary role for the
thermohaline circulation in driving the meridional heat
transport, and thus the oscillatory mode.
Keywords NAO � Ocean dynamics �North Atlantic decadal variability
1 Introduction
The North Atlantic Oscillation (NAO) is the primary var-
iability mode of the North Atlantic sector, characterized by
a redistribution of atmospheric mass between the Arctic
and the subtropical Atlantic (Hurrell et al. 2003). The
associated temporal variability is generally measured as
the normalized pressure gradient between Iceland and
Azores—the so called Hurrell’s NAO index (NAOI)—
displaying a broad spectrum of timescales, ranging from
interannual to decadal and longer.
While the reflections of NAO variability on other
components of the climate system are widely recognized
(Visbeck et al. 2003), there is no general consensus as to
whether changes, either intrinsic or NAO-forced, in the
oceanic state imprint back on the atmosphere, thus con-
tributing to the reddening of the NAO spectrum.
According to a simple interpretation (which is often
referred to as the climate noise paradigm; Madden 1981) it
is argued that the relevant spatial and temporal scales of
NAO are determined by processes which are intrinsic to the
atmosphere (Thompson et al. 2003). However, departures
from the climate noise null hypothesis are evident in the
spectrum of the observed NAOI (Feldstein 2000; but see
Wunsch 1999, for a discussion on their statistical rele-
vance). While the limited temporal extent of observational
records does not allow a clear interpretation of the NAO
decadal and interdecadal variability, considerable insight
can be gained from both theoretical inspection and
numerical experiments performed with models of varying
levels of complexity.
An unclear aspect concerning the NAO low frequency
variability is the role played by the ocean. Is the ocean
passively responding to the NAO-related atmospheric
A. Bellucci (&) � S. Gualdi � A. Navarra
Centro Euro-Mediterraneo per i Cambiamenti Climatici,
Viale A. Moro 44, 40127 Bologna, Italy
e-mail: [email protected]
S. Gualdi � E. Scoccimarro � A. Navarra
Istituto Nazionale di Geofisica e Vulcanologia,
Bologna, Italy
123
Clim Dyn (2008) 31:759–777
DOI 10.1007/s00382-008-0408-4
fluxes (Frankignoul and Hasselmann 1977) or does the
coupling with the overlying atmosphere determine
enhanced spectral power in both fluids at specific time-
scales? Numerical experiments performed with a hierarchy
of models with varying levels of complexity, but with
mostly idealized settings, show no unanymous answer
regarding the nature of ocean–atmosphere interactions in
the extratropical North Atlantic. Saravanan and McWil-
liams (1998) suggest that the ocean passively responds to
atmospheric variability at a preferred resonant decadal
time scale, set by a typical oceanic advective velocity and a
length scale determined by the dominant atmospheric
variability pattern. A similarly passive oceanic response to
unaltered NAO-like atmospheric fluctuations does also
emerge from Zorita and Frankignoul (1997) and Frankig-
noul et al. (2000) analyses of the low resolution flux
adjusted ECHAM1/LSG integration. Marshall et al. (2001;
hereafter M01) and Czaja and Marshall (2001; hereafter
CM01) based on a simplified theoretical model of the
extratropical North Atlantic coupled ocean–atmosphere
system, suggest that ocean dynamics introduce a significant
departure from the climate noise paradigm at decadal
timescales, with the ocean gyre circulation providing the
delay necessary to support a coupled oscillatory mode (a
mechanism which is generally referred to as the delayed
oscillator paradigm), thus extending to the Atlantic sector a
conceptual scheme widely used for ENSO studies, and also
adopted to inspect decadal variability in the North Pacific
(Latif and Barnett 1996).
Relying on a simplified numerical experimental setup is
appealing in that it allows to explore wide areas of a model
parametric space. On the other hand, the relevance to the
real system of results obtained through this approach can be
legitimately questioned. In the present study, the interplay
between ocean circulation and the NAO is addressed in a
twentieth century simulation conducted with a full-fledged
sea–ice ocean–atmosphere coupled GCM (CGCM), using
no flux corrections. The role of large scale ocean circulation
as a cross-basin heat carrier, and its impact on the low
frequency modulation of the mid-to-high latitude SST is
investigated. The relative role of the barotropic gyre versus
meridional overturning circulation in driving the poleward
heat transfer is also analysed. A mechanism governing the
oscillation is identified, bearing strong similarities with the
delayed oscillator paradigm proposed by M01.
The paper is structured as follows. In Sect. 2 we
describe the model used to perform the twentieth century
climate integration. In Sect. 3, the dominant modes of
variability of the analysed coupled system are illustrated.
In Sect. 4 we analyse the lead–lag relationships between
SST and NAOI. The NAO/ocean circulation interactions
are analysed with respect to both mass and heat transport,
in Sects. 5 and 6, respectively. A damped multiannual
oscillatory mode, and the underlying mechanism, are
skectched in Sect. 7. In Sect. 8, the magnitude of the
delayed oscillator parameters are derived from the coupled
model and compared with the estimates provided by CM01
and M01. A summary of the main results and final con-
cluding comments are reported in Sect. 9.
2 Model description and data
The model used for this study is the SINTEX-G (hereafter
SXG) coupled GCM (Gualdi et al. 2007). With respect to
the previous SINTEX and SINTEX-F versions (Gualdi
et al. 2003a; Gualdi et al. 2003b; Guiliardy et al. 2003;
Luo et al. 2003) the SXG model includes a thermo-
dynamic–dynamic snow sea–ice model (Fichefet and
Morales-Maqueda 1999), with three vertical levels (one for
snow, and two for ice).
We analyse results from a simulation of the twentieth
century, performed with forcing agents (including green-
house gases and sulfate aerosols) as specified by the IPCC
protocol for the 20C3M experiment (http://www-pcmdi.
llnl.gov/ipcc/about_ipcc.php). The main features of the
SXG 20C3M climate are documented in Gualdi et al.
(2007).
We restrict our analysis to the Atlantic sector, defined as
the [100W–0W; 0N–80N] longitude–latitude domain, with
a major focus on the boreal winter period (JFM), when the
NAO signature is expected to be more prominent (Hurrell
et al. 2003). In the present investigation, the whole length
of the 20C3M simulation, spanning the 1870–2000 period,
is used. All statistical moments have been calculated over
this time period. Winter anomalies were computed by
subtracting from each yearly JFM mean winter, the long-
term winter average computed over the whole JFM subset.
In the computation of empirical orthogonal functions
(EOF), a simple linear detrending has been applied to the
model data so as to remove the signature of the global
warming trend.
Since we are mainly interested in the coherency between
tropospheric and oceanic variables, throughout the paper
we will rely on lead–lag correlation (rather than regression)
patterns. We anticipate here that regression patterns for
several time-lags (not shown) reproduce the basic features
emerging from the correlation distributions shown.
3 Dominant patterns of oceanic and atmospheric
variability
We illustrate the temporal and spatial structure of the
model leading variability modes in the Atlantic sector by
resorting to a EOF analysis.
760 A. Bellucci et al.: NAO-ocean circulation interactions
123
The first EOF of wintertime sea level pressure (SLP;
equivalent to the model NAO) is shown in Fig. 1 (left
panel). Winter SLP variability (explaining 34% of the
variance) is dominated by a dipole structure, with a posi-
tive centre of action straddling the subtropics, and a
negative lobe approximately centred over Iceland, which is
grossly consistent with the main features of the observed
wintertime NAO (Hurrell et al. 2003).
A model NAO index is defined as the normalized dif-
ference between the JFM mean SLP spatially averaged
over two large areas, encompassing the dominant centres of
action: a northern subpolar box (50W–0W; 55–80N), and a
southern subtropical box (70W–0W; 30–55N). An NAOI
definition based on large areas averages is here preferred to
the more standard two-point approach since the former
allows a reduced dependence of the index on the migration
of the centres of actions (Stephenson et al. 2006). The
robustness of this NAOI definition has been tested against
changes in the zonal width of the (larger) southern box, by
progressively reducing the westward extent of this region,
but no relevant effects on the index were found. It is worth
to note that the model NAOI turns out to be almost
undistinguishable from the SLP leading principal compo-
nent (PC) (not shown). Similarly, the spatial pattern of
NAO obtained by linearly regressing SLP onto the NAOI,
shows negligible differences compared to SLP EOF1 (not
shown).
The model NAOI spectrum is compared with an
observed NAOI spectrum evaluated by using mean winter
(JFM) SLP station data from Iceland and Gibraltar for the
1870–2000 period (Fig. 2). We only focus on the interan-
nual-to-decadal timescale range, due to the poor resolution
of observed multi-decadal variability. The spectral power
was estimated using a Blackman–Tukey correlogram
technique (Blackman and Tukey 1958).
The model spectrum displays a bimodal structure, with a
broad-band peak around multiannual timescales (around
6 years) a narrower spectral signature around the quasi-
biennial period, and reduced power around 3–4 years. This
is fairly consistent with the power spectrum of the observed
NAO index, except that the latter shows more energy in the
near-decadal range. Also, the model appears to be sys-
tematically less energetic compared to observations, a
model bias which is shared by other state-of-the-art
CGCMs (Stephenson et al. 2006).
The leading EOF of winter SST (Fig. 1, right panel)
explains 29% of the variance and exhibits a tripole struc-
ture, with a warm anomaly in the western subtropical
Atlantic, a cold anomaly in the subpolar region and an
additional cold lobe in the tropics. Both the space structure
and amplitude of the leading SST mode are consistent with
the observed tripolar pattern dominating the wintertime
SST variability of the North Atlantic ocean (Cayan 1992).
Correlation between SST PC1 and NAOI is 0.5, statisti-
cally significant at the 95% level. A detailed lead–lag
covariance analysis between SST and NAOI is presented in
Sect. 4.
The vertical structure of the atmospheric response to a
positive phase of the NAO is diagnosed through a com-
posite analysis of winter (JFM) geopotential height (GPH)
anomalies at different pressure levels. Composites of GPH
anomalies for 850, 500 and 200 hPa keyed to the model
NAOI using a threshold of one standard deviation, are
shown in Fig. 3. The composite maps show that the 0-lag
free troposhpere response to a NAO+ event is equivalent
barotropic, with a positive (negative) GPH anomaly cor-
responding to the warm SST-high pressure (cold SST-low
pressure) NAO centre of action. This behaviour is consis-
tent with results obtained by Ferreira and Frankignoul
(2005) and D’Andrea et al. (2005) with a simple quasi-
geostrophic atmospheric model coupled to a slab ocean
mixed layer. Ferreira and Frankignoul (2005) describe the
equivalent barotropic response to a NAO-like SST anoma-
lous field as the result of transient eddy fluxes of
momentum and heat turning the initial baroclinic response
into a barotropic one.
90° W 60° W 30° W 0°
0°
15° N
30° N
45° N
60° N
75° N
SLP
90° W 60° W 30° W 0°
0°
15° N
30° N
45° N
60° N
75° N
SST
Fig. 1 (left) First EOF of boreal
winter (JFM) SLP (hPa). The
contour interval is 0.25 hPa.
(right) First EOF of boreal
winter (JFM) SST (�C). The
contour interval is 0.05�C. Solid(dashed) contours indicate
positive (negative) values. The
black thick contour indicates the
zero line
A. Bellucci et al.: NAO-ocean circulation interactions 761
123
The space structure associated with the leading temporal
scales of the SST tripole variability is now inspected in
detail. First we define an index of the temporal variability
of the tripole (which will be indicated hereafter as the
tripole index), and a natural choice is given by the SST
leading PC. In order to remove long-term fluctuations
(occurring over interdecadal-to-century scales) we referred
our tripole index against a moving background given by the
PC running mean computed with a 8-year time window
(Fig. 4). After selecting the years for which the tripole
index exceeds in absolute value 1 standard deviation (thus
identifying years characterized by high and low tripole
index, shown in Fig. 4) we average the winter SST
anomalies over the years with a high index and then sub-
tract the average computed over low index years, thus
obtaining a lag-0 composite map, reproducing the
previously described tripole pattern (Fig. 5). The compos-
ite map for the following 1 year-lag is obtained by
subtracting the low index +1 year average from the high
index +1 year average. The same procedure is reiterated
for several temporal lags. Statistical significance of the
composite maps has been estimated by resorting to a
bootstrap Monte Carlo methodology (Storch and Zwiers
1999), where a subset of winters randomly selected from
the full model data set has been used to generate an
ensemble of 1,000 surrogate composite maps. Anomalies
which have been found to occur less than 50 times (out of
1,000) are considered statistically significant at the 95%
level (also indicated in Fig. 5). The sequence of lagged
composite maps reveals that the tripole structure disappears
after 1 year but re-emerges 5 years later, with a reduced
amplitude. Since the thermal inertia of the mixed layer
accounts for an ocean memory of a few months (Frankig-
noul et al. 1998), the reappearance of the tripole a few
years later suggests that an additional process sustaining
the leading SST variability pattern must be at work. A
closer inspection of the composite maps also reveals
poleward propagating structures, with a tripole sign-
reversal occurring around lags +2 and +3 years. While the
reversed tripole pattern is not entirely significant at the
95% level (particularly in the subtropical region), it turns
out to be significant at the lower 90% level (not shown).
CM01 found a similar low frequency behaviour of the
SST tripole in the historical dataset assembled by Kaplan
et al. (1997). After keying winter SST anomalies to an
index measuring the meridional SST gradient across the
separated Gulf Stream (thus, not entirely independent with
respect to the tripole index used in the present study) CM01
found a reappearance of a reversed tripole (i.e., a tripole
with opposite sign) after 6 years, while the initial tripole is
recovered at lag 14 years (although the latter is not statis-
tically significant). These results are consistent with the
approximately 12 years spectral peak found by Deser and
Blackmon (1993) in an observational record of SST
10 9 8 7 6 5 4 3 2
0.5
1
1.5
2
2.5
3
Pow
er (
std2 )
PERIOD (years)
NAO−OBSNAO−SXGSST PC1−SXG
Fig. 2 Power spectra of observed NAO index (thick line), model
NAO index (thin line) and model SST PC1 (dashed line). All spectra
were computed using a Blackman–Tukey correlogram technique,
with a Bartlett window having a size equal to 1/10 of the total length
of the analysed time series. Since all time series are normalized, units
are in squared standard deviations
90° W 60° W 30° W 0°
0°
15° N
30° N
45° N
60° N
75° N
850 hPa
90° W 60° W 30° W 0°
0°
15° N
30° N
45° N
60° N
75° N
500 hPa
90° W 60° W 30° W 0°
0°
15° N
30° N
45° N
60° N
75° N
200 hPa
Fig. 3 Winter GPH anomalies (in meters) at (from left to right) 200,
500 and 850-hPa pressure levels. GPH anomalies were obtained from
a composite analysis keyed to the years where the NAOI exceeds one
standard deviation. Contour interval is 10 m. Solid (dashed) contoursindicate positive (negative) values. The black thick contour indicates
the zero line
762 A. Bellucci et al.: NAO-ocean circulation interactions
123
spanning the 1900–1989 time period. The multiannual
memory emerging from the model composite maps is
consistent with the power spectrum of the tripole index,
showing enhanced power around the 5 years period (shown
in Fig. 2). A discussion on the possible causes underlying
this mismatch between model and observed timescales of
the SST tripole will be provided in Sect. 7.
It is important here to stress that these results are robust
with respect to changes in the time window used to define
the moving background of the tripole index. Using 5 and
10 years for the time window width provided essentially
similar results (not shown). The multiannual variability of
the tripole pattern is further discussed in the following
section.
4 NAO/SST interactions: lead–lag analysis
In the present section the coherency between NAOI and
SST is investigated. Pointwise correlation maps of NAOI
against winter SST anomalies at lags from -4 to +4 years
are shown in Fig. 6 (the NAOI leads for positive lags).
From this analysis emerges that the interaction between the
leading atmospheric variability mode and SST occurs at
spatial scales which are basin-wide. The zero lag correla-
tion map shows the well known tripole pattern (consistent
1880 1900 1920 1940 1960 1980 2000−3
−2
−1
0
1
2
3
YEAR
SST PC1
Fig. 4 First PC of SST. Circles (stars) indicate years where the PC is
larger (smaller) than +1 (-1) standard deviation
Fig. 5 Composite maps of winter SST anomalies (in �C), based on
years where the normalized SST PC1 (the tripole index; shown in
Fig. 4) is high and low, with respect to a threshold of one standard
deviation (in absolute value). At lag zero, the composite is simply the
difference between the average SST anomalies computed over high
tripole and low tripole years. At lag +1 year (and similarly for larger
lags), the composite is computed by shifting the high and low tripole
index years by 1 year. Regions featuring a 95% statistical significance
level, according to a bootstrap Monte Carlo methodology (see text for
details), are encircled with a black thick contour
A. Bellucci et al.: NAO-ocean circulation interactions 763
123
with the leading SST EOF) indicating that the SST
response to a NAO+ phase is essentially local, through
changes in the turbulent heat fluxes, leading in turn to heat
loss/gain in the mixed layer (Cayan 1992). However, sig-
nificant correlation is also found at non-zero time lags. A
tripolar horse-shoe pattern (Czaja and Frankignoul 2002)
develops around lag -3 and reaches a maximum amplitude
at lag -2 years, while at positive time-lags (particularly at
lags +1 to +3 years) a delayed ocean response is evident
which appears to be determined by the slow poleward
propagation of correlation structures. Due to this slow drift,
changes in the subpolar basin surface temperature appear to
be related to an NAO+ event occurred 2–3 years before.
A closer inspection of lagged NAOI/SST correlation
patterns reveals that the propagating structures approxi-
mately follow the mean path of the Gulf Stream/North
Atlantic Current (GS/NAC) system, marked by the strong
climatological SST meridional gradient (Fig. 7). An Hov-
moller diagram along the main propagation route (Fig. 8)
reveals that SST anomalies with an amplitude of about 1�C
migrate from the subtropical region reaching the southern
tip of Greenland in about 2 years, and the Labrador basin
1 year later (but there are hints of an eastward propagation
route as well; see Fig. 7). The propagation bears strong
similarities with the observed migration of thermal features
described by Sutton and Allen (1997; hereafter SA97).
However, if the structure and path followed by the model
thermal anomalies substantially agree with the observa-
tions (within the limits of the GS/NAC representation in a
coarse resolution OGCM) , a large discrepancy emerges
with respect to the along-path propagation speed, which is
about 6 cm/s (estimated as 5,500 km/3 years), compared to
the much slower 1.7 cm/s estimated by SA97. Interest-
ingly, both model and SA97 estimate of propagation speed
are inconsistent with the observed near-surface current
velocities in the Gulf Stream, which can be larger than
1 m/s at some locations, suggesting that subsurface weaker
currents may be actually responsible for the drift of thermal
anomalies.
The existence of significant NAOI/SST correlations for
both positive and negative time-lags, suggests that the
ocean is not passively responding to the NAO, but changes
in the SST may feed back on the NAO. The 2 years time
taken for a sign reversal of the correlation pattern to occur,
Fig. 6 Correlation maps of NAOI against winter SST for several
time lags (indicated in the bottom left corner of each sub-panel). The
NAOI leads for positive lags. Correlation values are indicated with
colour shading. Thick black contours encircle regions which are
statistically significant at the 95% level, according to a t Student test
764 A. Bellucci et al.: NAO-ocean circulation interactions
123
is consistent with the results found in the composite ana-
lysis of the SST tripole pattern. The propagation speed of
SST anomalies is consistent with an oceanic advective
mechanism (typical horizontal velocity magnitudes in the
model upper 100-m layer are of the order of 10 cm/s;not
shown). If this is the case, then the multiannual re-emer-
gence of the tripole pattern would be determined by a
typical non-local process. The relationships between the
large scale (barotropic and overturning) ocean circulation
and NAO variability are inspected in the next section.
5 The role of ocean circulation
In this section, the interactions between NAO and ocean
circulation are investigated. We ideally split the large scale
ocean mass transport into a horizontal gyre component, and
a meridional overturning component. The gyre circulation
is diagnosed via the barotropic streamfunction of the ver-
tically integrated transport (in Sv; 1 Sv = 106 m3/s),
obtained by solving the Poisson equation with an iterative
method. The meridional overturning transport (which is
often identified with the thermohaline circulation) is
defined as the zonally integrated meridional transport
above a certain geopotential level (in Sv).
5.1 Gyre circulation
The mean horizontal circulation structure (Fig. 9, left)
reproduces in a realistic way the extratropical double-gyre
circulation pattern, with a subtropical gyre strength of
40 Sv, and a 20 Sv subpolar gyre. The barotropic circula-
tion is generally poorly observed but estimates of the
Florida Current strength (approximately coinciding with
the core of the subtropical gyre) provide a mean transport
90° W 60° W 30° W 0°
0°
15° N
30° N
45° N
60° N
75° N
LAG 0
LAG +1
LAG +2
LAG +3
0
5
10
15
20
25
30
Fig. 7 Regions of positive NAOI/winter SST correlation regions for
time-lags 0 to +3 years (white contour; statistically significant at the
95% level, according to a t Student test). Grey shading indicates the
climatological SST (in �C). The dashed white curve indicates the
dominant propagation path followed by thermal anomalies
TIM
E (
YE
AR
)
Along−track distance (km)0 1000 2000 3000 4000 5000
1870
1880
1890
1900
1910
1920
1930
TIM
E (
YE
AR
)
Along−track distance (km)0 1000 2000 3000 4000 5000
1940
1950
1960
1970
1980
1990
2000Fig. 8 Hovmoller diagram of
linearly detrended winter SST
anomalies along the track
indicated by the dashed line in
Fig. 7 (in �C). Left (right) panel
shows anomalies for the 1870–
1935 (1936–2000) time period.
Contour interval is 0.2�C. Greyshading is used for warm
anomalies
A. Bellucci et al.: NAO-ocean circulation interactions 765
123
of about 30–33 Sv, although large amplitude high-fre-
quency oscillations, around the mean, ranging within the
20–40 Sv range, have also been observed (Schott et al.
1988; Baringer and Larsen 2001). The dominant variability
mode of barotropic circulation (explaining 43% of the total
variance; Fig. 9, right) features a 5 Sv anomalous anti-
cyclonic gyre at mid-latitudes, which exhibits a core
shifted to the north with respect to the mean subtropical
gyre, while a weaker (3 Sv) cyclonic circulation anomaly
intensifies the background cyclonic circulation in the
western subpolar basin (Labradror Sea). The anomalous
gyre circulation is consistent with the inter-gyre gyre (IGG)
postulated by Marshall et al. (2001), reflecting a Sverdrup-
like vorticity balance between the NAO-induced wind-
torque and the meridional advection of planetary vorticity:
WSv ¼1
bq0
Zx
xE
ðr � sÞzdx0 ð1Þ
where b is the meridional gradient of planetary vorticity, q0
is a reference density, s is the wind stress vector, and Wrepresents the streamfunction of the vertically integrated
transport. Visbeck et al. (2003), using wind-stress obser-
vations combined with the Sverdrup relationship (Eq. 1)
provide a 6 Sv estimate of the IGG strength, which is fairly
consistent with the model IGG. The Sverdrup balance does
not hold close to the coastal boundary layer and nearby
complex topographic structures (as in these regions extra
terms in the vorticity budget may become as important as
the wind-stress torque), which may explain why in the
subpolar region the model gyre cyclonic anomaly is weaker
than the 8 Sv estimate of Visbeck et al. (2003).
The coherency between changes in the NAOI and the
horizontal gyre circulation is inspected through lead–lag
correlation maps (shown in Fig. 10; NAO leads for positive
lags). For negative time lags, correlation is generally low,
but there is a distinct signature of positively correlated
circulation anomalies in the subpolar basin, while the
subtropics are characterized by mostly negative correla-
tions, although not statistically significant (except for lag
-4 years). At lag zero, the barotropic circulation responds
to a positive phase of the NAO with an overall enhance-
ment of the transport at the subtropical/subpolar gyre
boundary. The correlation zero-line exhibits a north-eastern
tilt, suggesting enhanced transport across the mean inter-
gyre boundary, which has a more zonal orientation (shown
in Fig. 9, left). At the following time-lags, the northern
circulation dipole pattern observed at lag zero propagates
towards the western part of subtropical and subpolar
basins. Circulation anomalies appear to propagate from the
eastern North Atlantic to the North American sea-board in
approximately 3 years. Hints of further southward propa-
gation through coastally trapped boundary signals are also
visible (at +3 and +4 years time lags). Interestingly, the lag
+1 year pattern strongly resembles the leading EOF asso-
ciated with the horizontal circulation (shown in Fig. 9,
right). The detection of significant correlations for non-zero
time-lags, largely dirven by westward propagating features
suggests that baroclinic Rossby modes are responsible for
the adjustment of the barotropic wind-driven circulation to
the NAO-related wind forcing. The overall response of the
gyre circulation is consistent with the anomalous wind
stress pattern associated with the NAO (shown in Fig. 11).
A positive (negative) NAO phase is associated with a mid-
latitude anticyclonic (cyclonic) wind-curl anomaly and an
opposite sign circulation in the subpolar basin, which in
turn leads to a gyre equilibrium response that (at least in
the subtropics) can be largely explained by simple Sverd-
rup dynamics. The gyre spin-up occurs through
propagating baroclinic Rossby modes, setting the delay
timescale of the barotropic circulation (Anderson et al.
1979). A gross indication of the gyre spin-up timescale is
given by the time lag for which the correlation between the
NAOI and the leading PC of the barotropic streamfunction
90° W 60° W 30° W 0°
0°
15° N
30° N
45° N
60° N
75° N
Ψbar
EOF1
90° W 60° W 30° W 0°
0°
15° N
30° N
45° N
60° N
75° N
Ψbar
Mean
Fig. 9 (left) Mean barotropic
streamfunction (in Sv). Contour
interval: 10 Sv. (right) Leading
EOF of annually averaged
barotropic streamfunction.
Contour interval: 0.5 Sv. Solid(dashed) contours indicate
positive (negative) values. The
black thick contour indicates the
zero line
766 A. Bellucci et al.: NAO-ocean circulation interactions
123
is maximum, which yields a 1 year value (significant at the
95% level; not shown). A similar delayed response of the
horizontal circulation has been found in numerical experi-
ments performed with uncoupled ocean GCMs (Bellucci
and Richards 2006; Eden and Willebrandt 2001).
5.2 Overturning circulation
Next we focus on the response of meridional overturning
circulation to changes associated with the NAO. The long-
term mean of the Atlantic meridional overturning stream-
function in the depth-latitude space (Fig. 12) displays the
typical single cross-hemispheric cell, responsible for
northward transport of warm water in the upper 1,500 m,
compensated by a deep return flow of dense waters (the
model North Atlantic Deep Water), the two limbs of the
cell being connected by sinking taking place in the sub-
polar basin. The overturning reaches a maximum of 35 Sv,
Fig. 10 Correlation maps of NAOI against annual mean barotropic
streamfunction for several time lags (indicated in the bottom leftcorner of each sub-panel). The NAOI leads for positive lags. Solid(dashed) contours indicate positive (negative) values. Contour
interval is 0.05. The zero contour is not shown. Grey shading marksthe regions which are statistically significant at the 95% level,
according to a t Student test
260 270 280 290 300 310 320 330 340 350
10
20
30
40
50
60
70
80
0.1 N/m2
Longitude
Latit
ude
Fig. 11 Composite distribution of JFM wind stress anomalies
(in N/m2) corresponding to a positive phase of the NAO
A. Bellucci et al.: NAO-ocean circulation interactions 767
123
at a 1,500 m depth around 45�N. This is by far an over-
estimate of the available observations, indicating an
approximately 18 Sv strength for the Atlantic overturning
(Kuhlbrodt et al. 2007, and references therein), even when
the large uncertainties associated with the direct estimates
are taken into consideration. While this is a clear deficiency
of the present model, it must be emphasized that it is the
time-dependent part of the meridional overturning (and the
coherency with the NAO) to be relevant to the process
under examination, rather than the amplitude of the mean
state. Moreover, we anticipate here that the overturning
component of the large scale circulation appears to play a
relatively less significant role in orchestrating the coordi-
nated changes between NAO and ocean circulation
detected in the model.
Pointwise correlations between the NAOI and the
meridional overturning circulation are shown in Fig. 13.
Two distinct timescales govern the overturning response to
NAO. At lag zero, most of the signal is essentially deter-
mined by Ekman dynamics driving the shallow surface
flow cells associated with the NAO-related zonal wind-
stress anomalies. At non-zero time lags correlation patterns
reveal spatially coherent structures, involving changes in
the deep circulation. At lag +1 year, a dipole pattern
emerges. During a positive NAO phase, a deep clockwise
(counter-clockwise) overturning cell enhances (decreases)
the background meridional circulation in the subpolar
(subtropical) basin. The enhanced meridional overturning
and sinking in the subpolar basin points to the increased
high latitude buoyancy losses (which in turn lead to
anomalously cold SST) and convection during a positive
NAO phase as likely driving factors. For time lags +2 up to
+4 years the enhanced overturning region propagates
southward, while in the mean time a negative correlation
area (determining weaker overturning) starts to develope in
the subpolar area. At lag +4 years, the dipole initially
detected at lag +1, reappears with reversed sign. The sign
inversion of the dipole-like overturning anomalies can also
be traced for time lags -2 and +7 years (not shown),
although the associated correlations are below the 95%
statistical significance level. Thus, the overturning circu-
lation variability undergoes an oscillatory mode having a
typical 6 years period. The southward propagating over-
turning anomalies take about 4 years to reach the equator
from the subpolar generation region. This slow adjustment
of the thermohaline circulation indicates that advection of
convectively generated dense water is the primary cause of
the delayed response of the meridional overturning, in
agreement with the results shown by Marotzke and Klinger
(2000).
In general, the overturning anomalous flow does not
show any hemispheric structure, i.e., involving the whole
Atlantic conveyor, but it is rather localized in space. The
overturning dipole indicates that during a positive NAO
phase, the anomalous downward mass transport in the
northern part of the subpolar basin is compensated by
anomalous upwelling around 45�N.
The implications stemming from the differing gyre and
thermo-haline response to the NAO on the ocean meri-
dional heat transport will be discussed in the next section.
6 Meridional heat transport
In Sect. 4, we found evidence of poleward propagating
surface thermal anomalies along the path set by the model
Gulf Stream and its extension, which concurs to modulate
the northern part of the tripole over a 5 years time scale.
The slow propagation speed of SST anomalies suggests
that advection is likely to play a relevant role in this
process. As discussed in Sect. 5, both the gyre and over-
turning circulation show a lagged coherent response to the
NAO and are potentially involved in the poleward
migration of thermal anomalies. In order to elucidate the
relative importance of gyre and overturning circulation on
the meridional transfer of heat across the subtropical/
subpolar gyre boundary, we analyse the lagged correlation
between the NAOI and advective heat transport at 51�N,
grossly marking the climatological position of the high
latitude zero line in the mean gyre circulation. We
explicitly compute the total advective heat transport and
the contribution from the meridional overturning circula-
tion, while the gyre contribution is obtained as a residual
between the total transport and the overturning component
(Fig. 14).
The total and gyre heat transport reach a maximum
positive correlation at lag +1 years, whereas the
−30 −20 −10 0 10 20 30 40 50 60−4000
−3500
−3000
−2500
−2000
−1500
−1000
−500
0
0
0
0
0
0 0
3
3
3
3
333 3
6
66
6
6
66
9
9
9
9
9
99
12
12
12
12
1212
15
15
15
15
1515
18
18
18
18
1818
21
21
21
21
2121
24
24
24
24
24
2727 27
2727
27
30
30
30
30
33
33
LATITUDE
DE
PT
H
Fig. 12 Mean meridional overturning streamfunction (in Sv). Con-
tour interval is 3 Sv
768 A. Bellucci et al.: NAO-ocean circulation interactions
123
overturning component lags the NAOI by 2 years. The
correlation is found to be larger for the horizontal gyre
term, which closely follows the total meridional heat
transport. Significant correlations (at the 95% level) are
found for the total and gyre components only. The positive
lagged correlation indicates that for a positive (negative)
NAO phase, the lateral heat transfer across the subtropical/
subpolar gyre boundary is northward (southward). The
lagged correlation does also reveal a 5 years characteristic
time scale, suggesting that the meridional heat flow across
the inter-gyre boundary undergoes a damped multiannual
oscillation. There is a clear consistency between the lagged
response displayed by the advective heat transport terms
and the corresponding delayed adjustment exhibited by the
barotropic and meridional overturning circulation, shown
in the previous section. While in principle both the hori-
zontal and meridional overturning components of the large
scale circulation may concur to change the phase of the
SST tripole pattern, the present analysis suggests a major
role for the anomalous gyre circulation, driven by NAO-
forced wind curl anomalies. The secondary role of the
overturning circulation is likely due to the lack of a cross-
basin (hemispheric scale) thermohaline response to the
NAO, so that the northward heat transport is more effi-
ciently accomplished by the IGG circulation.
Fig. 13 Correlation maps of NAOI against annual mean meridional
overturning streamfunction for several time lags in the depth-latitude
space.The NAOI leads for positive lags. Solid (dashed) contours
indicate positive (negative) values. Contour interval is 0.05. The zero
contour is not shown. Grey shading marks the regions which are
statistically significant at the 95% level, according to a t Student test
−10 −8 −6 −4 −2 0 2 4 6 8 10
−0.2
−0.1
0
0.1
0.2
0.3
TIME−LAG (Years)
CO
RR
ELA
TIO
N C
OE
FF
ICIE
NT
TOTALGYREOVERTURNING
Fig. 14 Lagged correlation between NAOI and total (black thick),
gyre (dashed) and overturning (dotted) advective meridional heat
transport at 51�N.Circles indicate correlations which are statistically
significant at the 95% level, according to a t Student test
A. Bellucci et al.: NAO-ocean circulation interactions 769
123
7 Damped multiannual oscillation: a mechanism
The strong coherency characterizing several components of
the system under analysis, supports the idea that the
dynamics underlying the detected coordinated changes in
the NAO (via meridional redistribution of air mass), SST
and large scale mass and heat transport in the ocean are
essentially coupled. In the present section we sketch a
possible mechanism, favouring a scenario where the
anomalous gyre circulation (or IGG) is a preferred process
with respect to the meridional overturning.
During a positive NAO phase, enhanced surface
westerlies across the middle latitudes, combined with
stronger than average trade winds in the 10–30�N latitude
belt, determine an anticyclonic wind stress curl anomaly
straddling the extratropics between 30 and 50�N, while a
cyclonic surface circulation anomaly develops over the
subpolar region. The vorticity source associated with the
NAO wind-torque drives a Sverdrup response of the
barotropic wind driven circulation, leading to a mirror
anticyclonic IGG, enhancing the background subtropical
gyre circulation in proximity of the GS/NAC frontal sys-
tem. The IGG determines an enhanced meridional heat
transport across the subtropical/subpolar gyre boundary,
which in turn leads to the warming (cooling) of the sub-
polar (subtropical) basin. The consequent sign reversal in
the northern SST dipole, forces the NAO to enter into a
negative phase, through a positive NAO/SST feedback.
Once the NAO has stepped into a negative phase, the
previously described stages of the oscillation repeat with
reversed sign, and the oscillation completes its cycle.
According to this scheme, the gyre circulation is an
essential element of the coupled oscillatory mode, in that it
provides the delay which is crucial for sustaining the
oscillation. A combination of advective and wave dyna-
mics governs the negative feedback between the ocean
gyre circulation and NAO. The adjustment of the baro-
tropic IGG to changes in the wind stress curl occurs
through the propagation of baroclinic Rossby modes. The
gyre spin up is quite fast (order 1 year), but the lateral
transport is also affected by the (slower) advective process.
The effective timescale associated with the poleward
transport of thermal anomalies (i.e., the time taken by an
SST anomaly to propagate from the subtropical basin to the
subpolar basin) is of the order of 2–3 years.
In sketching the coupled mechanism we have assumed
that the northern SST dipole forces a NAO-like atmo-
spheric response, ultimately leading to sizeable changes in
the surface wind stress. The lead–lag correlation analysis
between NAOI and SST does indeed show significant
correlation for negative time lags, i.e., when the SST leads
the NAO. In particular, the correlation pattern emerging at
lag -2 years bears striking similarity with the so called
horse-shoe pattern described by Czaja and Frankignoul
(2002; hereafter CF) who analysed the lagged covariance
between SST and tropospheric anomalies in the NCEP-
NCAR reanalysis. In CF analysis, the horse-shoe pattern
precedes a NAO positive phase by several months. In our
analysis the intra-seasonal time scale is not considered, but
a similar covariability appears to work on the interannual
time scale. This is not entirely inconsistent with CF results,
which show that it is the long persistence (from summer to
winter) of the horse-shoe pattern to favour the onset of a
positive NAO-phase. A clear identification of causal rela-
tionships in observations as well as in CGCMs results
cannot be achieved by (even sophisticated) statistical
diagnostic tools, and further understanding of mid-latitude
SST forcing mechanisms of NAO has been gained through
numerical experiments (Peng and Whitaker 1999; Peng
et al. 2002, 2003). Rodwell et al. (1999) analyse the
response of an atmospheric GCM forced with observed
SSTs and show that SST anomalies re-enforce the thermal
and geopotential structure of the NAO, thus suggesting the
existence of a positive feedback (i.e., SSTs generated by
anomalous NAO-heat fluxes strengthen the wind stress
field which in turn feeds back on the SSTs). A potential
indicator of SST-induced atmospheric thermal heating is
provided by the 200-hPa GPH anomalies, which relate to
changes in the thickness of the troposphere. Figure 15
shows composite maps of 200-hPa GPH and SST winter
(JFM) anomalies, obtained for positive minus negative
phases of the SST tripole (as diagnosed through the pre-
viously defined tripole index). This is done at lags 0, +3
and +5 year, so that at lag 0, the composite is simply the
difference between the average SST and GPH anomalies
computed over high minus low tripole index years, while at
the following n-year lags, the composite is computed by
shifting the high and low index years by n years. The
200 hPa GPH anomalies exhibit (at lag 0) a deep low over
the subpolar region and a high over the subtropical region,
overlying cold and warm SST anomalies, respectively. The
same pattern re-emerges after 5 years with a weaker
amplitude, after going through a phase reversal at lag
+3 year. This result is consistent with Rodwell et al. (1999)
findings (see their Fig. 3e). The strong spatial and temporal
coherence displayed by these two fields suggests—with all
the due caveats concerning the identification of causality in
a CGCM—that ocean SSTs may impact, through diabatic
heating, not only on the lower troposphere, but—through
an equivalent barotropic response—on the upper tropo-
spheric layers as well.
In order to corroborate the hypothesis of a positive
feedback between mid-latitude SST anomalies and NAO,
additional AMIP-type experiments using the SXG atmo-
spheric model (ECHAM4 with T106 resolution) in stand-
alone configuration, forced with observed SSTs for the
770 A. Bellucci et al.: NAO-ocean circulation interactions
123
1956–2000 period were performed. We analysed monthly
outputs from a three-members ensemble of 44 years long
integrations to examine the atmospheric response to the
winter time (JFM) SST tripole. The model response was
calculated as differences of JFM 200 hPa GPH anomalies
between high and low extremes of a SST tripole index. The
SST index was defined as the difference between winter
anomalies in a northern subpolar and a southern subtropical
region, so as to capture the centres of action of the
observed SST tripole. The response is season dependent,
but a strong NAO pattern emerges in February-March-
April, with an amplitude of *30 m/K (Fig. 16). GPH
anomalies computed at 500 hPa (not shown) display a
*20 m/K response. These results are consistent with the
findings of Peng et al. (2002), who used a large ensemble
of experiments performed with the NCEP GCM with a T42
resolution. The fact that the same tropospheric variability
patterns found in the coupled framework were reproduced
in the uncoupled system indicates that mid-latitude SSTs
can indeed force a significant response in the present
atmospheric model.
The coupled oscillation is highly damped and this may be
due to the relatively small spatial extent of propagating
thermal anomalies in concomitance with the thermal
damping operated by turbulent air–sea fluxes. The coupled
oscillation is consistent with a stochastically forced delayed
oscillator model, with the delay essentially provided by the
gyre circulation. Marshall et al. (2001; hereafter M01)
developed a theoretical model which extends the stochastic
climate model of Frankignoul and Hasselmann (1977),
adding the effects of ocean dynamics. According to M01, a
privileged role is played by the wind-driven circulation,
with the anomalous IGG being considered a most efficient
heat carrier through the GS/NAC front, compared to the
meridional overturning. Once a feedback between SST and
wind-stress is allowed, the system behaves as a delayed
oscillator, with the delay set by the propagation of baro-
clinic Rossby waves (assumed to be of order 10 years). The
ocean–atmosphere coupling introduces enhanced power in
the surface temperature spectrum around the delay time-
scale, determining a major deviation from the essentially
red noise spectrum displayed by Frankignoul and Hassel-
mann (1977) model. Using the M01 theoretical model,
CM01 show that, when the coupling is considered, the
spectral structures found in the SST imprint on the wind
Fig. 15 Composite maps of winter 200 hPa GPH (contour) and SST
anomalies (colour shading), in m and �C, respectively, based on years
where the tripole index (shown in Fig. 4) is high, with respect to a
threshold of one standard deviation (in absolute value). At lag zero,
the composite is simply the average GPH (or SST) anomaly computed
over high tripole years. At lag +3 years (and similarly for lag
+5 years), the composite is computed by shifting the high tripole
index years by 3 years. Countour interval is 5 m. Solid (dashed) line
indicates positive (negative) values. The black thick line indicates the
0 line
Fig. 16 Composite map of February–April 200 hPa GPH (contour)
and January–March SST anomalies (grey shading), in m and �C,
respectively, computed over years where a SST tripole index exceeds
one standard deviation (high minus low index years; see text for
details). These results are from an ensemble of integrations performed
with ECHAM4 (T106) in a stand-alone configuration, forced with
observed SSTs for the 1956–2000 period. Contour interval is 5 m.
Solid black (white) contours indicate positive (negative) values. The
black thick contour indicates the 0-line
A. Bellucci et al.: NAO-ocean circulation interactions 771
123
stress power spectrum as well, showing enhanced vari-
ability over the same frequency range as for SST. The
mechanism emerging from the analysis of the SXG coupled
model qualitatively fits within the one outlined by M01. A
gross spectral consistency between the NAOI (essentially
capturing changes in the geostrophically balanced wester-
lies) and the SST leading variability mode is found in the
SXG model (Fig. 2), similar to the one shown by CM01.
Both NAOI and SST signals exhibit a bimodal spectral
structure, with enhanced power at quasi-biennial and multi-
annual periods. The broad multiannual spectral peaks
largely overlap, although the SST clearly peaks at 5 years,
while the former is centred around a slightly longer period.
Discrepancies between SXG and M01 model arise when
the essential timescales featured by the two systems are
compared. The adjustment of the IGG to changes in the
NAO (estimated as the time lag for which the correlation
between the NAOI and the barotropic streamfunction PC1
is maximum) takes place in about 1 year in the CGCM,
against the decadal timescale assumed by M01 and CM01.
However, if the time taken by gyre anomalies to propagate
across the zonal width of the Atlantic basin (as can be
inferred from Fig. 10, around 45�N) is considered, we find
a slightly longer *3 years timescale. This is still an
underestimate of the theoretical phase speed for the first
baroclinic Rossby wave, predicting a 8 years time-scale at
45�N (Killworth et al. 1997). Bellucci and Richards
(2006), using an uncoupled OGCM forced with a realistic
NAO-like wind-stress pattern, found a strong dependency
of the IGG spinup timescale on the ocean eddy mixing
strength, with a slow 4 years (fast 2 years) adjustment
under low (high) dissipative conditions. A thorough dis-
cussion on the limitations of state-of-the-art OGCMs in
correctly reproducing the planetary waves is beyond the
scopes of the present work. However, the high dissipation
which is needed to maintain the numerical stability in
coarse resolution ocean models (as in the present case) is
likely to impact on the correct representation of local
potential vorticity gradients, which may ultimately alter the
propagation speed of planetary waves.
It is interesting to contrast our results with those
obtained with experimental setup of intermediate com-
plexity (a detailed comparison between the coupled
oscillation found in SXG and the delayed oscillator
framework described by M01 and CM01 is presented in the
next section). Eden and Greatbach (2003) couple a OGCM
(having a horizontal resolution similar to the ocean model
used in SXG) to a simple stochastic atmosphere (described
in Bretherton and Battisti 2000) and find that the system
undergoes a damped decadal oscillation. However, unlike
the scenario postulated by M01 and the results from the
present analysis, the negative feedback which maintains the
oscillation is orchestrated by the overturning circulation
(providing the decadal timescale), while the IGG circula-
tion determines a positive feedback on the meridional SST
gradient, with the wind-driven circulation acting to actually
reduce the cross-gyre heat transport for a positive NAO
phase. Using a similar approach, D’Andrea et al. (2005)
analyse the impact of ocean heat transport on NAO with a
quasi-geostrophic potential vorticity atmospheric model
coupled to a mixed layer ocean model. The effects of ocean
dynamics on heat transport are parameterized so as to
mimic the M01 analytical model, with the ocean response
to changes in the NAO governed by a fixed 10 years
timescale. This highly constrained system produces an
oscillation in both atmosphere and ocean with a 15 years
period and a space structure bearing strong similarities with
the oscillation diagnosed in SXG coupled system. Differ-
ences between the dominant temporal scales in our system
and in D’Andrea et al. (2005) clearly reflect the assumption
made by the latter on the decadal adjustment of gyre cir-
culation to changes in the NAO.
8 Relationships between SXG and the delayed
oscillator model
8.1 The delayed oscillator: basic equations and scaling
factors
Here a more quantitative analysis of the mid-latitude
oscillatory mode is presented, essentially aimed to set the
coupled model behaviour within the parameter space of the
delayed oscillator framework, developed by M01 and
CM01. A complete derivation of this model can be found
in M01 and CM01. Here we will schematically refer to the
dimensional equations B.1 and B.2 in CM01 (here, Eqs. 2
and 3, respectively), in the hypothesis that the largest
contribution from ocean dynamics comes from the wind-
driven gyre circulation:
dDT
dt¼ �kDT � aN þ gwg ð2Þ
s ¼ N � f DT ð3Þ
Equations 2, 3 govern the interannual evolution of the
northern SST dipole DT (defined as the difference of SST
anomalies averaged over a northern and a southern box,
TN-TS) and the zonal wind stress anomaly s (defined as the
difference between anomalous westerlies and trade winds),
with N the stochastic component of surface wind stress, g
wg the heating rate associated with the anomalous heat
transport by the IGG, k-1 denoting a damping timescale for
DT due to air–sea interactions, and f the SST dipole
feedback on the zonal wind stress. After scaling Eqs. 2, 3
by the system relevant scales for time (td, related to the
propagation of baroclinic Rossby modes, around the IGG
772 A. Bellucci et al.: NAO-ocean circulation interactions
123
latitude), IGG strength (Wg), SST dipole ð� Þ and zonal
wind stress (swind), a new set of equations is obtained
which is formally identical to the previous one except that
now non-dimensional forms of g, f and k parameters
appear, defined as g� ¼ gtdWg��1; f � ¼ f� swind
�1 and
k* = k td. After invoking time-dependent Sverdrup
dynamics for the parameterization of wg, and neglecting
the stochastic wind forcing N in Eq. 3 (see CM01), Eqs. 2,
3, now regarded as non-dimensional, can be rephrased as a
delayed oscillator problem:
dDT
dt¼ �k�DT � f �g�DTðt � 1
2Þ ð4Þ
where the second term on the right hand side expresses the
dependency of the gyre advection term on the wind
induced by temperature anomalies during the previous
Rossby wave transit time. Equation 4 reveals that a par-
ticularly insightful parameter of the delayed oscillator is
R = f*g*/k*, weighting the efficiency of gyre dynamics in
transferring heat through the inter-gyre boundary (f*g*),
with respect to the damping of SST anomalies (k*) through
ocean–atmosphere interactions (incorporating both local
and Ekman-driven non-local processes). An estimate of R
determines whether damped (R \ 1) or growing (R [ 1)
oscillatory solutions are supported by the system. In order
to relate in a simple way the coupled model behaviour to
the simplified delayed oscillator system, we derive R from
the analysed SXG simulation, and compare it to the esti-
mates provided by CM01 and M01.
In the present study, the scale factors have been directly
estimated from the main features of the coupled model
20c3m simulation, yielding td = 3 years, Wg = 5 Sv,
swind = 0.07 Nm-2 and � ¼ 1 K: The temporal scale
factor td reflects the zonal propagation timescale detected
for horizontal circulation anomalies around the IGG lati-
tude (Fig. 10). The strength of the IGG was diagnosed
through the amplitude of the dominant variability pattern of
barotropic streamfunction (shown in Fig. 9b). For swind, an
average value of the zonal wind stress anomaly in the
westerly belt during a positive phase of the NAO, was
selected (see Fig. 11). An indicative 1 K value has been
adopted to scale DT, based on the typical north–south SST
gradient during a positive NAO phase. The boxes selected
to define DT in the model are (50�N–70�N, 60�W–30�W)
for the northern box, and (40�N–50�N,80�W–60�W) for the
southern box, and have been chosen so as to isolate the
centres of action of the NAO SST dipole.
8.2 Delayed oscillator parameters estimate
The estimate of the parameters contributing to the ampli-
tude of the R factor is performed by relying on a linear
regression approach.
Equation 2 is a linear model with one predictand _DT
(where the dot indicates the time derivative) and three
predictors DT, N and w. We assume that, over the inter-
annual timescales considered here, the stochastic
component of the surface wind stress N is instantaneously
uncorrelated with respect to the other terms in Eq. 2, as N is
by definition a white noise signal, while DT and w display a
red spectral signature. Thus, we estimate k and g by fitting
into a simplified version of Eq. 2 (i.e., after removing the
stochastic forcing term) a linear model:
Y ¼ b0 þ b1DT þ b2wg ð5Þ
with Y the predicted value for _DT ; and b1 and b2 yielding
the estimates for k and g, respectively. The left-hand side
term in Eq. 2 is evaluated using a centred finite difference
scheme, while wg is defined as the barotropic
streamfunction anomaly (i.e., obtained by removing the
long-term time-mean) area-averaged inside the core of the
IGG. The non-local nature of the dynamic (gyre) predictor
imposes to consider correlations at non-zero time lags.
Similarly, a simple lagged correlation between DT and _DT
displays an antisymmetric shape around lag 0, with
significant correlations at lags +1 and -1 year, and zero
correlation at lag 0 (not shown). We use the multiple
correlation coefficient R2 to evaluate the fit of the predicted
Y onto the observed _DT : Several predictand/predictors
time-lag relationships are considered (not shown) but a
maximum R2 = 0.5 fit is found for:
_DTn�2 ¼ �kDTn�1 þ gwn ð6Þ
where the n subscript indicates the temporal index. Thus,
the set of predictors DT and w accounts for about 50% of
the total variance of the predictand _DT ; when wg (DT) leads
the SST dipole rate of change by 2 (1) years. The corre-
sponding dimensional estimates for the gyre efficiency and
SST dipole damping rate are g = 0.025 K Sv-1 year-1 and
k = 1/(2.3 years) yielding the non-dimensional values
g� ¼ gtdWg��1 ¼ 0:38 and k* = k td = 1.3. The positive
value for g implies that an anticyclonic (cyclonic) gyre
circulation anomaly drives a positive (negative) DT thermal
contrast, i.e., the northern box becomes warmer (cooler)
compared to the southern box. The 2 years lagged corre-
lation reflects the poleward propagation time-scale
affecting surface thermal anomalies (Fig. 7).
In order to estimate the feedback of the SST dipole onto
the zonal wind stress f we make use of the AMIP set of
uncoupled atmospheric integrations, already described in
Sect. 7. Averaging over an ensemble of AMIP simulations
allows to better single out the atmospheric response forced
by the SST, from the response to the weather noise N,
different for each member, the latter approaching zero in
the limit of a large ensemble. It must be noted that a more
rigorous approach would have required the use of an AMIP
A. Bellucci et al.: NAO-ocean circulation interactions 773
123
ensemble forced with SSTs taken from the long coupled
simulation (while in the present case, an observed SST is
used). This approach, described in detail by Schneider and
Fan (2007), will not be pursued here. After linearly
regressing DT onto s (over a region in the northern North
Atlantic displaying significant cross-correlation) we obtain
an (ensemble mean) dimensional estimate f = + 0.029 N
m-2 K-1 indicating that a negative DT (colder than average
northern box and warmer than average southern box) is
consistent with a positive NAO phase (increased westerlies
and trade winds). The non-dimensional value is f � ¼f� swind
�1 ¼ 0:41: This estimate is also consistent with the
analysis performed by Neelin and Weng (1999) of the
zonal wind stress response of ECHAM2 atmospheric
model to SST anomalies in the North Atlantic (see their
Fig. 2), suggesting that f* can reach *0.4. We are now
able to estimate the parameter D = f*g* = 0.16, modulat-
ing the magnitude of the delay term (due to gyre dynamics)
in Eq. 4, and finally R = D/k* ^ 0.1.
The fairly low magnitude of D and R indicates that the
oscillatory mode detected in the coupled model is a strongly
damped one. In Table 1, we compare the parameter values
found in SXG with the estimates provided by CM01 and
M01 (where available). The coupled model parameters are
largely consistent with those provided by CM01 and M01,
except for g, which shows a considerably lower magnitude.
This leads to a consistently smaller R value, compared with
the estimates of CM01 (R = 0.4) and M01 (R = 1.6). The
scaling factors adopted to define the delayed oscillator
parameters (listed in Table 2) are clearly crucial in deter-
mining the size of R. Again, there is an overall consistency
between the scale factors diagnosed for SXG and the esti-
mates provided by CM01 and M01, except for td which in
SXG (and M01) is far shorter than in CM01. This dis-
crepancy relates to differences in the estimate of the IGG
adjustment timescale, which is in turn determined by the
phase speed of the first order baroclinic Rossby mode at a
mean IGG latitude. In CM01 an indicative 40�N latitude is
adopted, implying a *10 years propagation timescale
(Killworth et al. 1997). The rather shorter 3 years timescale
diagnosed for the SXG coupled model, despite the gross
consistency with the observed IGG structure and location
(CM01; Visbeck et al. 2003), may suggest a misrepresen-
tation of planetary waves in the coupled model.
Changes in the definition of the northern and southern
boxes appear to have a small impact on the magnitude of R.
Overall, even accounting for the uncertainties associated
with each single parameter, the resulting R = 0.1 estimate
appears to be a robust estimate. The low g magnitude is
clearly the most impacting factor, showing that the effi-
ciency of the wind-driven gyre circulation in sustaining the
oscillatory mode is strongly contrasted by the air–sea
damping of thermal anomalies.
9 Summary and conclusions
In this study the interplay between the large scale ocean
circulation and NAO was analysed with a full-fledged
CGCM. The model captures both the observed long-term
re-emergence of the SST tripole pattern (CM01) and the
propagation of surface temperature anomalies along the
path of the GS/NAC system (SA97). Based on the analysis
of the SXG 20C3M integration, it is argued that these fea-
tures of the extra-tropical North Atlantic SST variability are
strictly related to each other. The structure of the anomalous
gyre circulation suggests that the latter plays a dominant
role in the transfer of surface thermal features across the
inter-gyre boundary as well as in their following recircu-
lation within the western subpolar basin, which in turn
concurs to the low frequency changes in the northern part of
the SST tripole. On the other hand, the contribution of the
mean advection of temperature anomalies to the cross-gyre
heat transport is marginal as the mean flow acts along,
rather than across, the inter-gyre boundary, but its role is not
negligible in the subtropical gyre, where the mean flow
effects on the overall transport dominate. Significant lead–
lag covariance between oceanic and tropospheric variables
suggests that the system supports a damped oscillatory
mode involving an active ocean–atmosphere coupling, with
a typical NAO-like space structure and a 5 years timescale,
qualitatively consistent with the theoretical framework
developed by M01. The two essential processes governing
the oscillation are (1) a positive feedback between SST and
the NAO, and (2) a negative feedback between ocean gyre
circulation and the high latitude SST meridional gradient.
The existence of a significant atmospheric circulation
response to extra-tropical SST anomalies is further sup-
ported by additional AMIP-type integrations performed
with the SXG atmospheric model (ECHAM4) in stand-
alone configuration, forced with observed SSTs. The
atmospheric NAO pattern appears to have a weaker pro-
jection on the ocean meridional overturning, compared to
the gyre circulation, which leads to a secondary role for the
thermohaline circulation in driving the northward heat
transport, and thus the oscillatory mode.
A quantitative analysis of the mid-latitude oscillatory
mode, setting the coupled model behaviour within the
parameter space of the delayed oscillator framework,
shows that the efficiency of the wind-driven gyre circula-
tion is strongly contrasted by the air–sea damping of
thermal anomalies, yielding highly damped oscillations (as
quantified by a fairly low R = 0.1 factor), in accord with
the findings of CM01. The heavily damped nature of the
oscillation found in the SXG model sets a major difference
with respect to the mid-latitude unstable mode described by
Latif and Barnett (1994, 1996) for the North Pacific, and
later adapted by Grotzner et al. (1998) to the North
774 A. Bellucci et al.: NAO-ocean circulation interactions
123
Atlantic case, underlying the self-sustained decadal oscil-
lation found in an extended integration of the ECHO
coupled model.
An important consideration to be done is that, despite
the qualitative consistency with existing theoretical models
and observations, the relevant temporal scales charac-
terizing the present mechanism appear to be distorted by
deficiencies in the ocean component of the CGCM. In
particular, both the re-emergence of the tripole and the
poleward drift of SST anomalies take place over a shorter
timescale compared to the observations. This timescale
discrepancy determines enhanced coupled variability at
multiannual—rather than decadal—temporal scales. A
number of factors may contribute to this mismatch. First,
the anomalously fast gyre spin-up (with respect to what the
theory of baroclinic Rossby waves predicts at the latitudes
under exam) which is likely to be related to the relatively
high dissipation used in the OGCM. An additional reason
of concern is the oversized strength of the Atlantic con-
veyor, which may concur to enhance the background mean
flow and thus further reduce the advective time scale of the
ocean sub-system. These considerations point to the need
for including less dissipative ocean models (i.e., explicitly
resolving a larger fraction of the currently unresolved
physical processes) in next generation CGCMs, if we aim
to a proper representation of low frequency variability at
the extra-tropics. The recent availability of the AR4 IPCC
experiments makes possible to set the present results in the
wider context of a multi-model framework, and possible
extensions of this work, focusing on the impact of OGCM
horizontal resolution on the NAO/ocean circulation inter-
actions are currently under study.
Another important issue is the role of the seasonal cycle.
Throughout the paper we focused on winter time anomalies
as we were mostly interested in interannual-to-decadal
timescales, and winter is the season of the year featuring the
most powerful NAO signature, in both oceanic and tropo-
spheric variables. While an analysis taking into account the
effects associated with the seasonal variability was beyond
the scope of the present work, it is worth mentioning that the
seasonal cycle is likely to play an important role in the mid-
latitude delayed oscillator mechanism by affecting the year-
to-year persistency of surface thermal anomalies through
the winter re-emergence process described by Watanabe
and Kimoto (2000), ultimately affecting the damping rate of
SST anomalies (parameter k, in Eq. 2).
Finally, based on this set of results, we cannot rule out
other possible sources of uncoupled variability, i.e.,
involving intrinsic oceanic and atmospheric processes. A
complete assessment of the impact of ocean circulation on
the variability of the coupled system would probably
require an additional uncoupled experiment, where the
interactive ocean model is replaced with climatologically
varying SSTs. Compared to a standard AMIP type inte-
gration (where the atmospheric GCM is forced with
observed SSTs) this additional experiment would allow the
total removal not only of ocean dynamics but also of the
interannual changes of observed SSTs, which do include
the effects of ocean circulation embedded within. This will
be the subject of additional work.
Acknowledgements The authors wish to thank Riccardo Farneti
and Annalisa Cherchi for stimulating discussions and precious sup-
port. Comments from three reviewers considerably improved the
original manuscript. This work was supported by the Centro Euro-
Mediterraneo per i Cambiamenti Climatici (CMCC) Project and the
European Community ENSEMBLES Project (Contract GOCECT-
2003-505539).
References
Anderson D, Bryan K, Gill A, Pacanowski R (1979) The transient
response of the North Atlantic: some model studies. J Geophys
Res 84:4795–4815
Baringer M, Larsen J (2001) Sixteen years of florida current transport
at 27N. Geophys Res Lett 28:3179–3182
Bellucci A, Richards KJ (2006) Effects of NAO variability on the
North Atlantic Ocean circulation. Geophys Res Lett 33:L02612.
doi:10.1029/2005GL024890
Table 1 Summary of the delayed oscillator parameters in SXG, CM01 and M01
SXG CM01 M01
Dim Non-dim Dim Non-dim Dim Non-dim
k (2.3 year)-1 1.3 1 year-1 7 (1.6 year)-1 2.5
g 0.025 K Sv-1 year-1 0.38 n.a. 8 n.a. 10
f 0.029 N m-2 K-1 0.41 0.015 N m-2 K-1 0.3 n.a. 0.4
R = f*g*/k* 0.1 0.4 1.6
Table 2 Summary of the scale factors adopted to normalize the
delayed oscillator parameters in SXG, CM01 and M01
SXG CM01 M01
swind (N m-2) 0.07 0.05 0.05
� ðKÞ 1 1 1
td (year) 3 10 4
Wg (Sv) 5 10 10
A. Bellucci et al.: NAO-ocean circulation interactions 775
123
Blackman R, Tukey JW (1958) The measurement of power spectra
from the point of view of communication engineering. Dover,
Mineola
Bretherton C, Battisti D (2000) An interpretation of the results from
atmospheric general circulation models forced by the time
history of the observed sea surface temperature distribution.
Geophys Res Lett 27:767–770
Cayan D (1992) Latent and sensible heat flux anomalies over the
Northern oceans: driving the sea surface temperature. J Phys
Oceanogr 22:859–881
Czaja A, Frankignoul C (2002) Observed impact of Atlantic SST
anomalies on the North Atlantic Oscillation. J Clim 15:606–
623
Czaja A, Marshall J (2001) Observations of atmosphere ocean
coupling in the North Atlantic. J R Meteor Soc 127:1893–1916
D’Andrea F, Czaja A, Marshall J (2005) Impact of anomalous ocean
heat transport on the North Atlantic Oscillation. J Clim 18:4955–
4969
Deser C, Blackmon R (1993) Surface climate variations over the
North Atlantic during winter: 1900–1989. J Clim 10:393–408
Eden C, Greatbatch R (2003) A damped decadal oscillation in the
North Atlantic climate system. J Clim 16:4043–4060
Eden C, Willebrandt J (2001) Mechanisms of interannual to decadal
variability in the North Atlantic circulation. J Clim 14:2266–
2280
Feldstein SB (2000) The timescale, power spectra, and climate noise
properties of teleconnection patterns. J Clim 13:4430–4440
Ferreira D, Frankignoul C (2005) The transient atmospheric to
midlatitude SST anomalies. J Clim 18:1049–1067
Fichefet T, Morales-Maqueda MA (1999) Modelling the influence of
snow accumulation and snow-ice formation on the seasonal
cycle of the Antarctic sea-ice cover. Clim Dyn 15:251–268
Frankignoul C, Hasselmann K (1977) Stochastic climate models, part
II: applications to sea-surface temperature variability and
thermocline variability. Tellus 29:289–305
Frankignoul C, Czaja A, L’Heveder B (1998) Air-sea feedback in the
North Atlantic and surface boundary conditions for ocean
models. J Clim 11:2310–2324
Frankignoul C, Kestenare E, Sennechael N, de Coetlogon G,
D’Andrea F (2000) On decadal-scale ocean-atmosphere interac-
tions in the extended ECHAM1/LSG climate simulation. Clim
Dyn 16:333–354
Grotzner A, Latif M, Barnett T (1998) A decadal climate cycle in the
North Atlantic ocean as simulated by the ECHO coupled GCM. J
Clim 11:831-847
Gualdi S, Navarra A, Guilyardi E, Delecluse P (2003a) Assessment of
the tropical Indo-Pacific climate in the SINTEX CGCM. Ann
Geophys 46:1–26
Gualdi S, Guilyardi E, Navarra A, Masina S, Delecluse P (2003b) The
interannual variability in the tropical Indian Ocean as simulated
by a CGCM. Clim Dyn 20:567–582
Gualdi S, Scoccimarro E, Navarra A (2007) Changes in tropical
cyclone activity due to global warming: results from a high-
resolution coupled general circulation model. J Clim (in press)
Guilyardi E, Delecluse P, Gualdi S, Navarra A (2003) Mechanisms
for ENSO phase change in a coupled GCM. Clim Dyn 16:1141–
1158
Hurrell J, Kushnir Y, Ottersen G, Visbeck M (2003) An overview of
the North Atlantic Oscillation. In: Hurrell J , Kushnir J, Ottersen
G, Visbeck M (eds) The North Atlantic Oscillation: climatic
significance and environmental impact. American Geophysical
Union, Washington DC
Kaplan A, Kushnir Y, Cane M, Blumenthal B (1997) Reduced space
optimal analysis for historical datasets:136 years of Atlantic sea
surface temperatures. J Geophys Res 102:27835–27860
Killworth P, Chelton D, de Szoeke R (1997) The speed of observed
and theoretical long extratropical planetary waves. J Phys
Oceanogr 27:1946–1966
Kuhlbrodt T, Griesel A, Montoya M, Levermann A, Hofmann M,
Rahmstorf S (2007) On the driving processes of the Atlantic
meridional overturning circulation. Rev Geophys 45:1–32
Latif M, Barnett T (1994) Causes of decadal variability over the
North Pacific and North America. Science 266:634–637
Latif M, Barnett T (1996) Decadal climate variability over the North
Pacific and North America: dynamics and predictability. J Clim
9:2407–2423
Luo J, Masson S, Behera S, Delecluse P, Gualdi S, Navarra A,
Yamagata T (2003) South pacific origin of the decadal ENSO-
like variation as simulated by a coupled GCM. Geophys Res Lett
30, 2250. doi:10.1029/2003GL018649
Madden R (1981) A quantitative approach to long range prediction.
J Geophys Res 86:9817–9825
Marotzke J, Klinger B (2000) A study of the interaction of the North
Atlantic Oscillation with the ocean circulation. J Phys Oceanogr
30:955–970
Marshall J, Johnson H, Goodman J (2001) A study of the interaction
of the North Atlantic Oscillation with the ocean circulation.
J Clim 14:1399–1421
Neelin JD, Weng W (1999) Analytical prototypes for ocean-
atmosphere interaction at midlatitudes. Part I: coupled feedbacks
as a sea surface temperature dependent stochastic process. J Clim
12:697–721
Peng S, Whitaker JS (1999) Mechanisms determining the atmospheric
response to midlatitude SST anomalies. J Clim 12:1393–1408
Peng S, Robinson W, Li S (2002) North Atlantic SST forcing of the
NAO and relationships with intrinsic hemispheric variability.
Geophys Res Lett 29:1276. doi:10.1029/2001GL014043
Peng S, Robinson W, Li S (2003) Mechanisms for the NAO responses
to the North Atlantic SST tripole. J Clim 16:1987–2004
Rodwell M, Rowell D, Folland C (1999) Oceanic forcing of the
wintertime North Atlantic Oscillation and European climate.
Nature 398:320–323
Saravanan R, McWilliams J (1998) Advective ocean-atmosphere
interaction: an analytical stochastic model with implications for
decadal variability. J Clim 11:165–188
Schneider E, Fan M (2007) Weather noise forcing of surface climate
variability. J Atm Sci 64:3265–3280
Schott F, Lee T, Zantopp R (1988) Variability of structure and
transport of the florida current in the period range of days to
seasonal. J Phys Oceanogr 18:1209–1230
Stephenson D, Pavan V, Collins M, Junge M, Quadrelli R (2006)
North Atlantic Oscillation response to transient greenhouse gas
forcing and the impact on European winter climate: a CMIP2
multi-model assessment. Clim Dyn 27:401–420. doi:
10.1007/s00382-006-0140-x
Storch HV, Zwiers FW (1999) Statistical analysis in climate research.
Cambridge University Press, United Kingdom
Sutton RT, Allen MR (1997) Decadal predictability of North Atlantic
sea surface temperature and climate. Nature 388:563–567
Thompson D, Lee S, Baldwin M (2003) Atmospheric processes
governing the Northern Hemisphere Annular Mode/North
Atlantic Oscillation. In: Hurrell J, Kushnir J, Ottersen G,
Visbeck M (eds) The North Atlantic Oscillation: climatic
significance and environmental impact. American Geophysical
Union, Washington DC
Visbeck M, Chassignet E, Curry RG, Delworth T, Dickson R,
Krahmann G (2003) The ocean’s response to North Atlantic
Oscillation. In: Hurrell J, Kushnir J, Ottersen G, Visbeck M (eds)
The North Atlantic Oscillation: climatic significance and envi-
ronmental impact. American Geophysical Union, Washington DC
776 A. Bellucci et al.: NAO-ocean circulation interactions
123
Watanabe M, Kimoto M (2000) On the persistence of decadal SST
anomalies in the North Atlantic. J Clim 13:3017–3028
Wunsch C (1999) The interpretation of short climate records, with
comments on the North Atlantic Oscillation and Southern
Oscillations. Bull Am Meteor Soc 80:245–255
Zorita E, Frankignoul C (1997) Modes of North Atlantic decadal
variability in the ECHAM1/LSG coupled atmosphere-ocean
general circulation model. J Clim 10:183:200
A. Bellucci et al.: NAO-ocean circulation interactions 777
123