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The Relation between Decadal Variability of Subtropical Mode Water and theNorth Atlantic Oscillation*
TERRENCE M. JOYCE
Woods Hole Oceanographic Institution, Woods Hole, Massachusetts

CLARA DESER
Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, Colorado

MICHAEL A. SPALL
Woods Hole Oceanographic Institution, Woods Hole, Massachusetts(Manuscript received 14 October 1998, in final form 30 September 1999)
ABSTRACTThe Bermuda station ‘‘S’’ time series has been used to define the variability of subtropical mode water(STMW) from 1954 to 1995. This record, which shows decadal variability at a nominal period of about 12–14
yr, has been used as a baseline for seeking correlation with large-scale atmospheric forcing and with decadal
north–south excursions of the Gulf Stream position defined by the subsurface temperature at 200-m depth. A
common time period of 1954–89 inclusive, defined by the data sources, shows a high degree of correlation
among the STMW potential vorticity (PV), Gulf Stream position, and large-scale atmospheric forcing (buoyancy
flux, SST, and sea level pressure). Two pentads with anomalously small and large STMW PV were further
studied and composites were made to define a revised North Atlantic Oscillation (NAO) index associated withthe decadal forcing. During years of low PV at Bermuda, the NAO index is low, the Gulf Stream is in a southerly
position, and the zero wind stress curl latitude is shifted south as are the composite extratropical winter storm
tracks, in comparison to the period of high PV at Bermuda. Because the NAO, Gulf Stream separation latitude,
and STMW PV variations are in phase with maximum annually averaged correlation at zero year time lag, theauthors hypothesize that all must be either coupled with one another or with some other phenomenon that
determines the covariability. A mechanism is proposed that could link all of the above together. It relies on thefact that during periods of high STMW PV, associated with a northerly Gulf Stream and a high NAO, one finds
enhanced production of mode water in the subpolar gyre and Labrador Sea. Export of the enhanced Labrador
Sea Water (LSW) component into the North Atlantic via the Deep Western Boundary Current can influence theseparation point of the Gulf Stream in the upper ocean once the signal propagates from the source region to
the crossover point with the Gulf Stream. If the SST signal produced by the 100-km shift of the Gulf Stream
along a substantial (1000 km) length of its path as it leaves the coast can influence the NAO, a negative feedback
oscillation may develop with a timescale proportional to the time delay between the change of phase of the air–sea forcing in the Labrador Basin and the LSW transient at the crossover point. Both a simple mechanistic
model as well as a three-layer numerical model are used to examine this feedback, which could produce decadaloscillations given a moderately strong coupling.

1. Introduction
The most prominent type of subtropical mode water(STMW) in the North Atlantic is the 188C water (Wor-* Woods Hole Oceanographic Institution Contribution Number
9888.
Corresponding author address: Dr. Terrence M. Joyce, Woods Hole
Oceanographic Institution, Mail Stop 21, 360 Woods Hole Road,
Woods Hole, MA 02543.
E-mail: tjoyce@whoi.edu

q 2000 American Meteorological Society

thington 1959) found to the south of the Gulf Stream
in the Sargasso Sea. This layer lies above the permanent
pycnocline and is characterized by a vertically homogeneous layer that outcrops in late winter and is cappedover during spring. Its temporal variability has beenstudied using the time series at Bermuda by Talley andRaymer (1982) and recently updated by Talley (1996),
who noted some key characteristics (Talley 1996, Table2): mean depth 5 287 m, mean potential density 5
26.45 kg m23 , and mean potential temperature and salinity of 17.888C and 36.5 psu, respectively. Joyce andRobbins (1996) noted that the variability of the potential
vorticity, PV 5 2( f/r) r z , at 300-m depth (near mean

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FIG. 1. Distribution of potential vorticity 3 10212 (ms)21 on thepotential density surface 26.5 kg m23 according to Lozier et al. (1995).
A Gaussian spatial filter of 700 km has been applied to the gridded
data before contouring. Bermuda is located at the ‘‘1’’ mark within
the minimum.

depth of STMW at Bermuda) was anticorrelated withsurface density changes. Thinking of purely diabatic
processes for the formation of the STMW, one would
have to make the near surface density larger in order
to convectively mix the STMW, consistent with observations.
We expand on this theme in this study, first using thepotential vorticity (PV) variability of the STMW from
Joyce and Robbins and comparing this to decadal variations in the wintertime buoyancy flux at the surface
and then to other atmospheric fields, including sea levelpressure (SLP), which will inevitably invoke a patternreminiscent of the North Atlantic Oscillation (NAO). A
revised NAO index, keyed to the correlation with thePV signal will then be obtained. Finally, we will explore
the nature of the atmospheric and oceanic signal in different NAO/STMW ‘‘epochs,’’ concluding with comments on why the two signals are phased as they arewith some speculation on a possible coupling mechanism.
2. STMW variability and correlation with air–sea‘‘forcing’’
We begin by noting that our data source for the atmospheric side of the interface is the da Silva and Levitus (1994) atlas of Consolidated Ocean–Atmosphere
Data Sets, while the oceanic signal is predominantly
from the station ‘‘S’’ time series at Bermuda, beginningin 1954 and extending to the present. The period of
overlap of the two datasets is 1954–89, the last year
available in da Silva et al. In a study of the historicalhydrographic data in the North Atlantic, Lozier et al.

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FIG. 2. Bermuda’s station S time series of annually averaged STMW
PV at 200-m depth according to Joyce and Robbins (1996). Five yrof extreme low and high values used in pentadal analyses are denotedby ‘‘*.’’ In this and other figures, we have suppressed the leading“19” before the dates, all of which are in the twentieth century.

(1995) presented property maps of pressure, temperature, and PV on the 26.5 s u surface, nearly coincident
with the core density of the STMW. The PV signal isreproduced here in Fig. 1 using a 700-km Gaussian filter
similar in scale to that in da Silva et al. The PV distribution has an isolated minimum in which the island of
Bermuda is located. Surrounding this minimum is higher PV water in the Gulf Stream to the north and therecirculation gyre to the south. This fact suggests thatin the presence of downgradient eddy fluxes of PV, someprocess must be maintaining the minimum, namely, contact with the atmosphere and diabatic forcing in winter.
We will return to this later, but point out that the Bermuda data is particularly well located for the monitoringof long-term variations in the STMW PV because, located well within the minimum, lateral gradients are
small and horizontal advection of existing gradients by
the ambient, mean, and time-dependent circulation isminimal. The PV signal at Bermuda (Fig. 2) is here seen
to have a range of a factor of 2 from a low value near
5 3 10211 to 10 3 10211 (ms)21 . This signal clearlyshows decadal-type variations, with a climatologicalminimum value in 1964 and a maximum in 1975. We
will later focus on these two extreme time periods inorder to better understand the surface forcing.
Since the STMW lies sandwiched between the surface
layer and the pycnocline, we might first look to thepycnocline depth as a major contributor to STMW thickness changes, especially since the pycnocline represents
the maximum level of temperature and salinity variability in the water column (Joyce and Robbins 1996).
A correlation coefficient value of 20.07 between thetwo, however, is far below a zero significance value of
0.3 for the time series. We can therefore reject the hypothesis that pycnocline depth, perhaps associated with

2552

JOURNAL OF CLIMATEinterannual changes in wind stress curl (Sturges andHong 1995), is responsible for the STMW thickness or
PV signal.
We have correlated the PV time series at Bermuda
with the wintertime (January–March) atmospheric datafor buoyancy flux, SST, and SLP (Fig. 3, left panels).
Within the western subtropical gyre, PV and buoyancy
flux are negatively correlated; when the buoyancy flux
is positive, the ocean gets denser and the PV decreases.
The buoyancy flux anomaly in the Labrador Sea is positively correlated with PV at Bermuda; in fact, the correlation coefficient is largest just east of Newfoundland.
Dickson et al. (1996) have noted that time periods oflarge buoyancy flux in the Labrador Sea are associatedwith periods of low buoyancy flux in the Sargasso Sea
and it is not surprising that the STMW signal reflects
this. Cayan (1992) also showed the same phase difference between the eastern and western subtropics as we
find, but using the NAO index as a metric, not the
STMW variability. We note the overall spatial similarity
between the SST and buoyancy flux patterns and thatthe western subtropical gyre is cold when PV is low
and warm when PV is high (Fig. 3, middle panels), witha maximum SST response not in the region of the
STMW forcing to the northeast of Bermuda (see buoyancy flux composite anomaly), but rather near where
the Gulf Stream is located ‘‘upstream’’ of the maximum
buoyancy forcing. Because of the significant correlation
between the PV signal and the SST off the U.S. East
Coast, there is a similarity in the time series of PV andthe SST anomaly in the storm formation region (SFR)
shown by Sutton and Allen (1997). However, 1965, a
year of low PV at Bermuda is not a year of low SST
in the SFR, so there are some differences (The SLP
composite discussed next is different in the two analyses). The sense of the correlation of the STMW PV
and the SLP (Fig. 3, lower panels) reaffirms the importance of the NAO; with extrema located between
Greenland and Iceland in the north and southwest of the
Azores in the subtropics. We have shown all correlations
with no time lag, but have examined the sensitivity to
the atmosphere leading or lagging the ocean by 1 yr.
The correlation coefficient is reduced in both cases fromthat at zero lag. Thus, the STMW is responding ‘‘inphase’’ with the atmosphere, at least in terms of interannual anomalies.

VOLUME 13

defined warm and cold pentads based on the pycnocline
history at Bermuda in order to maximize our signal-tonoise ratio and to see the spatial structure of the oceanic
anomalies throughout the North Atlantic. In our case,we will use the STMW PV signal and look for anomalies
in the atmospheric forcing.
We first examine the buoyancy flux (Fig. 3, upper
right panel) that is closely tied to the PV forcing. During
low PV years, the maximum buoyancy forcing is to thenortheast of Bermuda, a region where the STMW isthought to form (Fieux and Stommel 1975). In contrast,
the buoyancy anomaly during high PV years is negativein the Sargasso Sea with a total swing of about 3 31025 kg (ms 3 )21 between the two extrema. We also show
SST and SLP anomalies for the low-minus-high PV
years (Fig. 3, middle and lower right panels) and remarkthat the SST is anomalously cool throughout the western
subtropical gyre with an amplitude of about 20.58C. In
the low-minus-high composite, atmospheric pressure islower near the Azores and higher between Greenlandand Iceland by about 9 and 13 mb, respectively. We
have not shown the net heat flux, but it behaves verymuch like net buoyancy flux, but with a different sign.
In fact, the contribution of the salinity forcing to thebuoyancy flux reinforces the net heat flux within thewestern subtropical gyre, but is generally smaller; in
low PV years the ratio of these two terms is 0.05, while
it is 0.32 in high PV years. If buoyancy (or heat) flux
is driving SST variability as is suggested by the workof Cayan (1992) and Deser and Timlin (1997), one
might expect the composite SST pattern to reflect thatof the composite forcing. The shifting of the SST signal‘‘upwind’’ of the forcing and not downstream in termsof oceanic advection may suggest (ignoring spatial variations of mixed layer depth) more than a simple passive
response of the ocean to the atmosphere. We have also
examined the point by point correlation between net heat
flux and SST anomalies in the region. Over most of theregion they are positively correlated, supporting the hypothesis of ocean following atmosphere. However, in
the region where the Gulf Stream leaves the coast, thecorrelation is negative. This suggestion of ocean leading
atmosphere was noted by Battisti et al. (1995) using asimilar dataset and demonstrated by Halliwell (1998)
using an ocean GCM.
4. A revised NAO index

3. Air–sea exchange during two climatologicalextrema
We will now examine the atmospheric conditions during the two climatological extrema in the STMW PV.
We select (based on Fig. 2) the 5 yr of minimum PV(1964–66, 1969, and 1970) predominantly in the 1960s
with 5 yr of maximum PV in the 1970s (1972–76). We
have not selected the 1981 period of low PV because
it was an isolated event in time. Our desire here is to
use these ‘‘pentads’’ very much like Levitus (1989), who

The low-minus-high PV composite pattern for SLP(Fig. 3, lower right) is very similar to Hurrell’s (1995)
NAO pattern, except that the subtropical Atlantic centeris shifted about 308 farther west and about 58 farther
south. It is also shifted about 108 east compared withthe composite pattern of Sutton and Allen (1997). Using
the SLP composite as a guide, we constructed a revised
NAO index, defined as the normalized SLP in the Icelandic area minus that in the subtropics. The NAO andnormalized PV records are plotted in Fig. 4, both un-

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FIG. 3. Correlation coefficient (dashed for negative, solid for positive) for STMW PV withbuoyancy flux (upper left), SST (middle left), and SLP (lower left). Contour interval is 0.1. The
95% significance level varies spatially due to changes in the integral timescale of the fields. In
general, this level varies between 0.45 and 0.5 over most of the region. For low-minus-high PV
pentads, the wintertime anomalies of buoyancy flux [upper right, contour interval is 0.5 3 1025
kg (ms 3 )21 ], SST (middle right, contour interval 0.28C), and SLP (lower right, contour interval
1 mb). Dark gray areas indicate positive anomalies and correlations. The position of Bermuda isdenoted by ‘‘1.’’

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FIG. 4. Normalized PV (solid lines) and wintertime NAO index(dashed lines). (top) Unsmoothed and (bottom) has 1–2–1 filter applied.

smoothed (top) and smoothed with a 3-point binomial
filter in time (bottom). The match is quite good in theunsmoothed records, except that there is an upward
trend in the NAO that is not present in the PV record(this aspect is even more apparent in the smoothed version). The correlation between the smoothed (unsmoothed) NAO and PV is 0.76 (0.70) up through 1990.
The lagged correlation of the unsmoothed NAO and PV
time series clearly indicates a maximum correlation atzero lag. We will discuss this further after we discuss
the Gulf Stream in the next section. If the years 1990–
95 are included, the unsmoothed correlation of 0.70 is
reduced to 0.52, owing to the increase in NAO index
in recent years with little change in the STMW PV.
Talley (1996) has presented a similar visual comparisonof NAO and PV records, but did not quantify thestrength of the relationship.
5. Gulf Stream path from subsurface thermal data
To investigate the issue of interannual changes in Gulf
Stream position, we have used subsurface temperature
data from the Levitus (1994) atlas of MBT and XBTdata for the common time period of 1954–89. The temperature at 200-m depth has been used for some time
as defining the region of strong flow of the Gulf Stream

VOLUME 13(Fuglister 1955). The 158C isotherm at 200 m, representing an isotherm in the center of the strong horizontal
gradient of the Gulf Stream, lies just to the north of the
maximum flow at the surface (Fuglister 1963) and is aconvenient marker for the northern ‘‘wall’’ of thestream. This has been confirmed by the time series of
Halkin and Rossby (1985) near 738W in which temperature and velocity profiles were placed in a streamoriented coordinate system and averaged. Since themaximum depth of the wintertime mixed layer west of
608W in the region is less than 200 m (Qiu and Huang
1995), this depth is not directly affected by diabatic
processes. Though the 158 isotherm surfaces north of
the Gulf Stream in winter, the property and velocity
variations on the outcropping isopycnals in the upper
ocean remain large for 2000 km after the Gulf Stream
leaves the coast (Bower et al. 1985), making this estimate of Gulf Stream location [T(200) 5 158C] relatively
unaffected by surface diabatic processes. Use of a deeper level (e.g., 300 m) produces similar results, but effectively eliminates the first decade of our time series
since the mechanical bathythermograph dataset did notextend that deep. Rossby and Gottlieb (1998) have examined repeated velocity sections made across the Gulf
Stream near 708W from 1993 to mid-1997. They havefound little interannual variability in the surface velocity, transport of the high velocity core, and the width
over time, while they have observed interannual changes
in the latitude of the flow. Thus, the dominant observable in the interannual variability of the surface Gulf
Stream is its location. We will now examine this using
the archive of subsurface temperature observations.
In the region of interest, between latitudes of 338 and
438N and between the longitudes of 458 and 768W, a
total of 7059 (3300) observations were found during thelow (high) PV period. The results have been presented
first at a selected longitude (658W), taking all available
data within 62.58 of longitude, and plotting the timeseries of 200-m temperature (Fig. 5, top). We have chosen this longitude because it is one of large interannual
variation in the Gulf Stream path (bottom). The timeseries shows north/south oscillations of the Gulf Streamthat look very similar to the NAO index above (Fig. 4)
and confirms a southward shift of the Gulf Stream during low NAO periods and a northward shift (comparedto the long-term mean) during high NAO periods. Looking south of the stream, we also see that when the stream
is south, the T(200 m) temperatures are low, with theobverse holding when the stream is north. The thermal
signals in the Sargasso Sea cannot be induced by shifts
in the Gulf Stream path, but must be due to enhanced
cooling/heating in the Sargasso Sea as discussed by
Molinari et al. (1997). The phasing of the air–sea forcing
and the subsurface temperatures are such as to reinforce
the sign of the anomaly (Deser and Blackmon 1993)
over the areas of the North Atlantic away from the Gulf
Stream. The envelope of annual Gulf Stream positions
is based approximately on 1000–2000 observations per

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FIG. 5. Annually averaged temperature at 200-m depth vs latitude and time (top) with a contour
interval of 28C. Temperatures less (greater) than 158C are shaded in light (dark) gray. The envelopeof 36 annual positions of the Gulf Stream based on T(200) data from 1954–89 (bottom). The
annual mean position is based on the 158C isotherm at 200 m. Also shown are the locations where
subsequent EOF analysis was done using the T(200) dataset. EOF analysis east of 608W did notindicate any contribution to the lowest (common) EOF mode.

year and shows a growing meandering pattern downstream from Hatteras (Fig. 5, bottom). There is a suggestion of a node near 688W, which is close to that foundnear 698W by Cornillon (1986) using satellite SSTbased 2-day maps of GS path over a 30-month period.
We can see that certain longitudes (e.g., 658W, 578W)
have a larger envelope of variability than others.
We also show the mean path of the Gulf Stream,
defined by the T(200 m) temperature during the 5-yr
pentads of low and high PV at Bermuda (Fig. 6, upper
panel) that shows a difference in mean position depending upon the PV signal at Bermuda. The total latitudinal range is about a half degree over most of theregion from where the stream leaves the coast to about
608W, with a slightly larger range of about 100 km near
658W, where we have shown a selected time series.
There is a significant difference in the Gulf Stream path
between 628 and 728W during the two periods.
Clearly a north/south shift in the Gulf Stream position
will create temperature anomalies at 200-m depth aswell as at the ocean surface without any atmosphericintervention. The sense of the observed shift is such thatenhanced cooling over the Gulf Stream–Sargasso Sea
during the low PV epochs will reinforce the SST andsubsurface temperature signal due to Gulf Stream position. The fact that maximum temperature differences

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FIG. 7. Gulf Stream index for coordinated north–south shifts inposition based on nine selected points along the Gulf Stream path
between 758 and 558W and the temperature at 200-m depth. The
covariance (not correlation) matrix for the nine temperature points
was used to construct the EOFs, in which more than 50% of theinterannual variance was contained in north–south changes of thesame sign at all nine locations. Periods when the GS is north havepositive values for the index. Also shown are the smoothed NAO
and STMW PV indices (Fig. 4, bottom) for the same time period.

FIG. 6. Mean position of 158C isotherm for two pentads of low
and high PV (upper panel) and zero wind stress curl (lower panel).
In both cases the standard error in the mean was used to construct a
significance (1 s) envelope for each of the two periods. Considerable
more variance was found in the wind curl data. In both panels, heavy
solid (dashed) lines denote low (high) PV pentads.

at 200-m depth between the two periods are often foundnear the position of the Gulf Stream suggests that boththe oceanic response to enhanced cooling together withthe southerly Gulf Stream position are acting in concert
to generate SST and upper ocean thermal anomalies overa longitudinal distance of almost 1000 km. One might
anticipate a similar situation in the North Pacific along
the Kuroshio Extension, although model/data comparisons there have focused mainly on changes in thestrength of the westerlies and gyre circulation and the
SST fields (Latif and Barnett 1994).
Halliwell and Mooers (1979) used 2 yr of Gulf Stream
frontal analysis data in their study of GS variability.
While their work focused on monthly timescales, they
did suggest that large-scale shifts of the position were
one of the dominant modes of interannual variability.
This has been further studied by George and Taylor(1995) and Taylor (1996) in the context of zooplankton
variability in English lakes. Their hypothesis is that Gulf
Stream (GS) position will affect atmospheric forcing
over the British Isles (although they considered mainly
SLP as an index, not buoyancy or heat flux) and thus
when lakes will stratify in the spring. Winters of highheat loss or buoyancy flux should be correlated withenhanced nutrient input into the surface layer, a delayed
restratification and with elevated zooplankton concentrations in late spring. Since southerly GS positions areassociated with enhanced STMW formation, above-average wintertime forcing over the Sargasso Sea and theUnited Kingdom (see Fig. 3, upper panel), suggests thatan important source of atmospheric variability existsthat would explain the zooplankton record. Taylor andStephens (1998) develop further the idea that coordinated north–south shifts in the Gulf Stream on interannual timescales are correlated with the NAO.
In order to better compare our results with theirs, wehave selected 9 locations along the Gulf Stream path
between 758 and 508W and used an EOF analysis of theT(200 m) data to determine an index for the Gulf Stream
position (these positions are shown in Fig. 5, bottom;
they coincide with the mean path of the Gulf Stream
based on the 158 isotherm). Based on the yearly averages, the time series (Fig. 7) of the most energetic mode
(more than 50% of variance) represents an in phasenorth–south shift in position that is correlated (r 5 0.7)
with our NAO index (Fig. 8) with maximum correlation
at lag 0 and 11 yr (GS following the NAO). A similar
result is obtained when the standard NAO index (normalized SLP difference between the Azores and Iceland)
is used in place of our ‘‘revised’’ NAO index (notshown). We note that this result differs from that of
Taylor and Stephens (1998) who used a Gulf Stream
index based on monthly frontal analyses of satellite SST
imagery during the period 1966–96. They found a maximum correlation when their GS index lags the NAO

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FIG. 8. Time-lagged cross correlation of the three variables shownin Fig. 7 was done over their common time period of 1955–89 inclusive. We find the largest correlation at zero years lag for all pairs,
except for the GS–NAO where the cross correlation is high for bothzero and 1-yr lag of the GS compared to the NAO. Significant correlations must exceed 0.45–0.5 for the three combinations, whichsuggests that the GS and PV are not directly linked to each other,
only through the NAO.

by 2–3 yr. As shown in the appendix, our GS index andthat of Taylor and Stephens (1998) are very similar from1975 onward (and yield similar lag correlations with theNAO), but disagree prior to 1975. We attribute the difference between the two GS records in the early years
to peculiarities in the frontal analysis product, although
we cannot substantiate this claim. Given the strong simultaneous correlation between our index of the GS andthe NAO, we do not interpret the NAO as simply forcing
a delayed response in GS position (as do Taylor andStephens 1998), but leave open the possibility that thetwo may also vary in phase.
6. Wind variability and the zero wind stress curl
location
Steady, homogeneous, linear and nonlinear models of
the wind-driven circulation (Pedlosky 1979) indicatethat the point of separation of the western boundary
current from the coast is governed by the latitude of thezero wind stress curl or the latitude at which the westward interior flow feeding the western boundary current
vanishes. While other factors control the point of separation in the real ocean, we thought it worthwhile toshow how these variables vary in time for the Gulf
Stream. We have used the da Silva data to estimate thewind stress curl and hence the interior Sverdrup transport and plotted this as a function of time near the west-

2557

FIG. 9. Transport (Sv) required at the western boundary to return
the Sverdrup interior flow at three selected latitudes near the westernboundary. This assumes a quasi-steady balance and is shown only toindicate the variability in the wind forcing and the latitude dependence
near the latitude of maximum Sverdrup transport.

ern boundary (758W) for three latitudes. At this longitude, the north wall position is at about 35.58N (Fig.
5, bottom). The maximum in the Sverdrup transport(plotted with opposite sign in Fig. 9) occurs at 33.58N
and one can see that despite an interannual standard
deviation of 64 Sv (1 Sv ; 10 9 kg s21 ) about the yearlymean values, the interior Sverdrup flow is always westward into the boundary current south of 33.58N, but iseastward at the latitude of the GS north wall (after separation). From 33.58N, the transport drops off more
quickly toward the north than the south. In fact, the gyreboundary, defined by the latitude of the zero wind stresscurl, is rapidly approached and nearly coincident withboth the maximum in the meridional Sverdrup transport
and the zero wind curl latitude at the western boundary.
The near coincidence of these with the position of theseparated Gulf Stream is a feature that Behringer et al.
(1979) attributed to an enhancement of the zonal windstress over the warm, surface GS water. For the low(high) PV years when the mean Gulf Stream location
is to the south (north), the zero wind curl position (Fig.
6, bottom) is also to the south (north). We therefore seeboth a small difference (at the 95% level) in the winddriven forcing at 33.58N during the low/high PV epochs:
25.2–27.8 Sv, as well as a significant difference in thelatitude of the zero curl line downwind of the Gulf
Stream shift. If the zero curl line also defines the positionof the maximum westerlies, then one sees them shifting
meridionally with about the same magnitude and witha similar (but displaced) longitudinal structure as theGulf Stream, during the different STMW epochs.
The Taylor and Stephens work, which found a delay
between the Gulf Stream latitude and the NAO index,
made use of a paper by Gangopadhyay, Cornillon, and2558

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Watts (1992, hereafter GCW). They used a Parsons–Veronis two-layer model with the lower layer at rest to
study the Gulf Stream separation latitude, which wasestimated locally near the coast in GCW as the latitude
where the GS path crossed the 2000-m isobath. A delayed, wind-driven response in the two-layer case wassuggested by GCW in good agreement with the observations for the period 1979–88. The sense of this estimate is that a larger Ekman transport (high NAO)
translates into a lower latitude of separation at a timelag associated with the long, baroclinic Rossby wave
adjustment (several years). For the time period of theirstudy, this phase lag results in the Gulf Stream being
in a northern position when the NAO index is high. We
show later that a similar delay in the Gulf Stream position may result from consideration of the thermohaline
circulation, which is not included in the model of GCW.
7. Atmospheric storm track variability
To further characterize the low level atmospheric circulation during low and high PV winters, we have investigated storm track variability based upon a datasetof extratropical cyclone frequencies (U.S. Navy andDept. of Commerce, 1996) obtained from the National
Climate Data Center (NCDC). The cyclone positions(based upon sea level pressure and given to the nearest
tenth of a degree) were binned into 28 3 28 grid boxes
and total area-weighted counts formed for each winterseason (January–March) during the period 1966–95.
The storm frequencies were further smoothed in thezonal and meridional directions with a 3-point binomial
filter.
The distribution of cyclones for the low and high PV
winters is shown in Fig. 10 superimposed upon the corresponding SST fields. Since only 3 yr (1966, 1969–70) contribute to the low PV composite, we have multiplied the storm frequencies by five-thirds to allow fora direct comparison with the high PV composite; there
are no significant differences in the total number ofstorm counts in the two periods after normalization. In
the low PV winters, the storm track is most intense along
the Gulf Stream between Cape Hatteras and Newfoundland. East of 508W, the cyclones move nearly due eastward toward Europe, with little storm activity north ofapproximately 508N. In the high PV composite, thestorm track extends northeastward from Cape Hatteras
towards Iceland. Rogers (1990) presented qualitatively
similar storm frequency distributions based on nine winter months with extreme NAO values.
The difference in storm frequencies (Fig. 10, lower
panel) between low and high PV winters has been superimposed on the mean storm frequency based on thewhole period 1966–95. Relative to the low PV years,
high PV years exhibit significantly more storms in thenortheast Atlantic and significantly fewer storms to thesouth. In high PV years, there is also a reduction in thenumber of storms over the Gulf Stream, the main region

FIG. 10. Cyclone count totals for the high (upper panel) and low(middle panel) PV composites normalized to 5 yr showing shades ofgray (with a contour interval of 2) for the number of wintertime
storms in a 28 3 28 box and contours for the associated composite
wintertime SST (from Reynolds). Cyclone count differences (low–high, contour interval is 2) for the two wintertime composites areplotted on top of the distribution of mean storm track distribution
based on the 1966–95 period, but shown for an average 5-yr period(lower panel). Shaded regions denote significantly higher or lower
storm counts compared to the mean.

of Atlantic cyclogenesis. The latitudinal distribution ofstorm totals over the Gulf Stream for the low and highPV winters is shown in Fig. 11. The maximum storm
frequencies are greater and located approximately 28
farther south in the low PV years compared to the highPV years. This latitudinal shift in storm activity is reminiscent of the north–south shift in the Gulf Stream position documented in section 5.
The pattern of storm frequency change (Fig. 10) is15 JULY 2000

2559

JOYCE ET AL.

8. Discussion
We summarize the anomalous conditions during low
and high PV years for the STMW in Table 1. Next weturn to some dynamical issues which emerge as a resultof the various correlations associated with the quantities
in the table.
a. Why are PV variability and forcing in phase?
Suppose PV is a quasi-conservative quantity obeying
an equation of the following formd(PV)/dt 1 lPV 5 F,

FIG. 11. For each of the two composite periods, storm track distributions have been plotted against latitude for a longitude band of
678–558W. The solid line is for low PV years and dashed line fordenotes high PV years.

broadly similar to that shown in Serreze et al. (1997);
however, the latitudinal shift in storm track location
along the Gulf Stream was not apparent in their analysis.
We recognize that the results presented in Figs. 10, 11
are based on a small sample size. To confirm the cyclone
count signals associated with the NAO, we performeda regression analysis between the full storm frequency
inventory and the NAO records based on the period
1966–95 with similar results (not shown) to those basedon the more limited high and low PV composites. The
most obvious relation between the effects of storm
tracks and the ocean signal is the enhanced cooling of
the STMW in the Sargasso Sea during a southerly storm
track and enhanced cooling of the Labrador Sea Water(LSW) due to cold air outbreaks on the back side oflows travelling on a more northeasterly storm track. The
storm track and associated large-scale atmospheric circulation may in turn be sensitive to the SST anomalies,in particular to shifts in the position of the Gulf Stream
via changes in air–sea heat fluxes (cf. Venzke et al. 1999;
Rodwell et al. 1999).

(1)

where lPV represents a relaxation process and F diabatic forcing. The form of the equation is chosen tofollow the Frankignoul and Hasselmann (1977) investigation of long-term SST signals generated by air–sea
forcing. For a subsurface, isolated, low PV anomaly incontact with the atmosphere over part of the year/region,
downgradient eddy fluxes of PV will contribute to l.
We have already noted that pycnocline displacement is
uncorrelated with PV variability of the STMW, thus we
do not expect vertical advection of PV to play a significant role. In fact, since the vertical gradient of PV
at the depth of the STMW vanishes, vertical advection
at that level vanishes altogether. Similarly, if mean horizontal flow lines are parallel to constant PV lines (consistent with the Lozier et al. PV and streamfunctionmaps), then mean horizontal advection is also not a
factor. The remaining terms are time rate of change,
forcing, and dissipation. In this limit, the low-frequency
response of the above will be such that lPV 5 F, and
the PV and forcing fields are in phase. For shorter timescales (or higher frequencies) the balance becomes (PV) t
5 F, and PV lags F in phase by 908. The fact that
diabatic forcing and PV variability of the STMW arein phase, suggests that l k (1 yr)21 and the system ishighly damped on annual timescales, much like SST. If
the forcing is diabatic and the relaxation process is eddy
flux of PV with a mixing coefficient of k (Rhines andYoung 1982), then the highly damped balance in (1)can be approximated2k¹ 2 PV 5 2f
B ,gr0 H 2 f(2)

where we have now replaced the idealized forcing withTABLE 1. Summary of results for low and high STMW regimes.
Property
Potential vorticity
Buoyancy flux anomaly
SST
DSLP (Azores–Iceland)
Gulf Stream position
NAO
Storm tracks

Low PV years of STMW
ø5 3 10211 (ms)21#2 3 1025 kg (ms3)2120.68C # SST , 0
212 mb # DP , 0South of mean location
Low phase
More zonal, southerly tracks

High PV years for STMW
ø10 3 10211 (ms)21$22 3 1025 kg (ms3)21
0 , SST # 0.58C
0 , DP # 9 mb
North of mean location
High phase
More northeasterly tracks with max near Iceland

2560

JOURNAL OF CLIMATETABLE 2. Parameters used in (3) to determine required lateralmixing for the quasi-steady PV balance of STMW.
PVa(m21 s21)

R (km)DR (km)f (s21)H (m)Bf[kg(ms3)21]

5 3 10211

700

200

1024

300

1 3 1025

terms for the Coriolis frequency f, layer thickness H,
and surface buoyancy flux B fa as presented above in theda Silva et al. atlas. Integrating (2) around a circle ofradius R and recognizing that any constant can be subtracted from PV (such as a ‘‘background’’ value) leads
to the following

kPVa 5 2RDR f
B ,2 gr0 H 2 f a(3)

where the subscript ‘‘a’’ refers to the PV or buoyancy
flux anomaly (relative to an ‘‘outside’’ value), DR is thescale over which the radial gradient in PV is estimated(at radius R), and B fa has been averaged over an areapR 2 . The time series at Bermuda can be estimated togive PV a , the da Silva et al. atlas can provide the buoyancy flux anomaly, and the Lozier et al. distribution of
PV (Fig. 1) gives R and DR leaving only k to be determined. We have done this using the values in Table
2 and have estimated an eddy mixing coefficient, k 5
1.5 3 10 3 m 2 s21 .
We could easily change the value of k by changing
the area over which the buoyancy flux acts to be different from the total area of the circle of radius R, representing the fact that the layer is in direct contact withthe atmosphere over only a fraction of the surface area.
In this case, the estimate of k would be reduced by thesame fraction. As an order of magnitude balance, however, it would seem that diabatic forcing equated to eddy
fluxes is plausible since the above estimate of k is notunreasonable based on other studies of mesoscale mixing in the ocean (Robbins et al. 2000, Joyce et al. 1998).
Our analysis differs from the balances considered byHazeleger and Drijfhout (1998) in their model of thesubtropical gyre in that they find that summertime detrainment of the mode water into the mixed layer ismore important than eddy fluxes. However, their model
did not resolve the eddies and had little recirculation of
the STMW near Bermuda, so our estimate should beconsidered an upper bound on k. They also find plausible variations in STMW PV based in interannual variations of the heat flux over a period from 1954 to 1978,
which spans our two pentads.
b. A new mechanism for a coupled oscillation
If the Gulf Stream position is responsible for a significant part of the atmospheric forcing, then a possiblemode of coupled oscillation may exist for creating selfsustained decadal signals of the sort we have been describing. We first begin in the Labrador Sea, at the end

VOLUME 13of the mixed layer deepening cycle that occurs in the
subpolar gyre (McCartney and Talley 1982). Pickart etal. (1997) have found that during cold winters, convective mixing on the periphery of the Labrador Basin iscapable of producing a type of LSW that is injected
directly into the western boundary current. During thesecold years, LSW is renewed within the Labrador gyreas well. They contrast two years (1966, low heat loss;
1972, high heat loss) in which maximum cooling rates
in the winter months vary by a factor of 2 between the
two years. The reader will note that these two years are
in different pentads for the STMW as well. In 1966(1972), heat and buoyancy fluxes were large (small) in
winter in the subtropical gyre consistent with the correlations presented in Fig. 3. Enhanced LSW productionand export in years in which the GS position is northof its mean position, the NAO is in a high phase, andSTMW is in a low phase encapsulates the decadal variability in the western North Atlantic based on our findings above.
For the North Atlantic, two important mechanisms
are needed to complete the necessary ingredients for aself-sustained oscillation: the air–sea forcing anomalies
must be coupled to GS position and the enhanced southward transport of LSW must influence the separation
point of the GS off Cape Hatteras. The nature of theatmospheric response to SST anomalies in the Gulf
Stream region remains controversial. Atmospheric general circulation modeling experiments by Palmer andSun (1985), Peng et al. (1995), and Venzke et al. (1999)
find a consistent response that resembles the observed
SLP anomaly pattern (i.e., Fig. 3). However, not all
GCMs obtain such a response (cf. Kushnir and Held
1996 for a review). Recent work by Peng et al. (1997)
suggests that the nature of the response depends sensitively upon the representation of feedbacks between
the transient eddies and the mean flow, an aspect thatis affected by model resolution and quality of the simulated mean climate. In addition, the presence of highinternal atmospheric variability in midlatitudes complicates the detection of a relatively weak atmospheric response to extratropical SST anomalies (cf. Venzke et al.
1999). Very recently, Rodwell et al. (1999) have simulated a realistic pattern and amplitude of the NAO in
an ensemble integration of a high resolution atmospheric
GCM forced by a pattern of SST anomalies in the North
Atlantic that closely resembles the observed pattern associated with the NAO (similar to that shown in Fig.
3). While not allowing any atmospheric feedback to theocean, nor taking into account that much of the SST
signal is produced by the atmosphere, their study suggests that midlatitude SST signals can influence the atmospheric circulation and the phase of the NAO. Theirstudy did not isolate the effects of SST anomlies along
the Gulf Stream path, however. These issues notwithstanding, we wish to explore a simple model in which
SST anomalies arising from changes in the Gulf Stream

15 JULY 2000

JOYCE ET AL.

path affect the atmospheric circulation in the sense depicted in Figs. 3 and 10.
The influence of transport variations of the Deep
Western Boundary Current (DWBC) on Gulf Stream
separation was clearly revealed to occur in the layered
numerical model of Thompson and Schmitz (1989).
They found that the addition of a southward transportof the DWBC moved the separation point of the Gulf
Stream southward in their model. This will be discussed
further in the next section. Spall (1996a,b) further
showed that the presence of a DWBC of LSW could
produce decadal variations in Gulf Stream position,
deep transport in the recirculation gyres, and the eddies
that create them even with a steady southward flow. In
these studies, a key diagnostic is the transport of the
LSW at the crossover point (Pickart and Smethie 1993)
that is far downstream of the Labrador Sea and, which
will reflect a time-lagged response to the forcing in the
Labrador Basin.
If the volume transport of LSW, represented by V,
which is exported due to air–sea forcing, F is represented as belowt Vt 1 V 5 F,

(4)then the steady-state balance reflects the net productionof LSW. A time-dependent forcing will change the rateof outflow with a response time t according to (4). The
anomalies of transport and forcing, defined by the departure from the steady-state values, are denoted with
subscripts a. At the crossover point, the anomaly of the
Gulf Stream position, y a , is related to the time-lagged
transport anomaly of LSW, Va (t 2 t 0 ), in the following
manner:y a 5 2kVa (t 2 t 0 ),(5)where k is a positive constant and the sign is such thata positive transport anomaly will move the separation
point southward. Finally, we relate the anomalous forcing to the unlagged position of the Gulf Stream:F 5 ry,(6)where r is another positive constant reflecting the observed fact that during periods when the Gulf Stream
is in a northern (southern) position, the wintertime cooling in the Labrador Basin and subpolar gyre is strong(weak). Finally, we combine (4)–(6) to obtain the following:t Vt 1 V 1 bV(t 2 t 0 ) 5 0,

(7)where all variables have had their a subscripts dropped
and we define b 5 kr. The relationship in (7) represents
a negative, delayed feedback between the volume transport that increases in time due to forcing but, which
will ultimately be decreased due to the southward shiftof the Gulf Stream once this information is received at
the crossover point. The value of b represents thestrength of the feedback. For small time lags, the feedback term stabilizes the solution, while for larger lags,

2561

oscillations can occur. This type of system was shownby Pippard (1985) to be stable in time for small enoughvalues of b, but to possess oscillatory and eventually
exponentially growing solutions when b is increased
beyond a value of 0.025. Since the important parameters(b, t , t 0 ) define the nature of the solution, we will briefly
discuss plausible values for these first.
Mean estimates of the transport of the DWBC
(Schmitz and McCartney 1993) are 12 Sv, of which 4
Sv are LSW. Pickart and Smethie (1998) find greater
values for both at 558W: 19 and 6 Sv, respectively. The
latter estimates from 1993 and 1995 represent a highphase of the NAO and suggest that there might be longterm variability in the classical LSW transport, although
this is just a conjecture at this stage. The recent measurements do not find a large recirculation indicating it
may be absent at that longitude or possibly missed in
the sections, in which case there may be less of a discrepancy between the two different estimates attributable to time dependence. As the recent measurements
are tied to some direct velocity measurements, we willtake these as representing a maximum in transport. We
hypothesize that the range of air–sea forcing in the Labrador Basin is such as to double or completely suppress
new production of LSW, the transport of the deeper
components of the DWBC being held constant. Thus,
the total transport in the LSW is 3 6 3 Sv. This may
seem extreme, and in fact there is no observational timeseries of LSW transport to guide us, but we will soonsee in this simple model that smaller ranges in interannual transport may still trigger oscillations. We haveobserved a variation in GS position of order 100 km so
we take an amplitude of 650 km to be associated witha transport change of 63 Sv as representing scales withwhich to nondimensionalize (4)–(7). The above sensitivity (0.06 Sv km21 ) is consistent with what is foundbelow in a more detailed three-layer numerical calculation. Thompson and Schmitz underestimated the sensitivity because they had only two layers, with the lower
layer four times thicker than the LSW layer we use
below. Since only the product kr is dynamically important, we will take it to be the ratio of the latitude
excursion and transport scales (17 km Sv21 ). When inserted into (4), using (5)–(6), we see that a value of 1
for b, corresponds to a transport change of 6 Sv due toa latitude change of 100 km. Since, according to Pippard, even small values of b lead to oscillations, onlya modest degree of coupling between air–sea exchange,
hence, transport change to Gulf Stream position is capable of making for nontrivial solutions of (7). We willconsider values of b in the range 0.01–1.
Curry et al. (1998) have shown that changes in LSW
thickness in the source region can be detected in thesubtropical gyre 6 yr later at Bermuda. The pathway is
not direct; in fact, LSW anomalies can be seen bifurcating near the tail of the Grand Banks with an eastward
pathway into the subpolar gyre and a second pathway
in the DWBC toward the crossover point near Cape

2562

JOURNAL OF CLIMATEVOLUME 13

Hatteras. Signals appearing at Bermuda must have followed the latter path and we expect that time delays ofa few years might be reasonable to reach the crossover
point. The LSW transport decay timescale t , represents
how long the Labrador Sea takes to reach a new steadystate. We simply take this to be a number in the range
of 1–5 yr and look at the nature of the solutions.
First, one can look for purely oscillatory solutions to(7) (imaginary part of frequency is zero) and show thatthe lowest frequency of oscillation is given by

vt 0 5 cos21 (1/b),(8)which cannot exist for b , 1. Since we are interested
in small b, we expect the relevant solutions be complex
in nature. We can solve the coupled equations (4)–(6)numerically from an initial state of zero anomalies, and‘‘force’’ the system by adding some random white noise
to the GS position. For small enough coupling we see(Fig. 11), as predicted by Pippard, that no oscillation
develops. For larger values of b, a self-sustained oscillation develops whose period is independent of b, butwhose amplitude is linearly related to b. Even for small
amplitudes of oscillation, the character of the solution
is periodic, but distinctly nonsinusoidal. In appears to
be a mode that for t 0 sufficiently greater than t , approaches a quasi-steady value corresponding to one of
the two extreme states of the system at the peak of eachhalf cycle, before being switched into another exponential mode that brings it back toward zero and thenovershoots to the other extreme. The period of this cycling is almost entirely determined by the time delay,
having a value of about 2.5t 0 , with (t , b) not playing
any major role in its determination. The nature of thelimit cycle in Fig. 12 is such that the GS will attain its
northern (southern) extreme, the transport will continue
to grow (decay) until a delayed signal appears at thecrossover point triggering a switch in the GS position
to the other state. The solution is more sawtoothed whent ø t 0 . This negative feedback oscillator can produce
decadal oscillations, requires coupling between theocean and atmosphere, and is consistent with the variability as encapsulated in Table 1. It clearly oversimplifies the real ocean, but is perhaps of some interest to
those seeking mechanisms for determining the natureand cause of the NAO. It is a close analog to that suggested for El Niño–Southern Oscillation (ENSO) by
Suarez and Schopf (1988), who also found that the period of their oscillator was about 2.5t 0 as we have here.
The novel aspects of this oscillator are that the position
not transport of the Gulf Stream is a key. Only processes
that occur in the western boundary region are important;no crossbasin oceanic Rossby wave propagation (Latif
and Barnett 1994) or downstream advection of temperature anomalies (Groetzner et al. 1998) is involved although both oscillatory modes require an atmospheric
response of increased (decreased) westerlies over a cold
(warm) SST anomaly.

FIG. 12. Normalized position of Gulf Stream (dashed) and normalized LSW transport (solid lines) for three different values of thecoupling term b as indicated on the figure panels. The values of(t 0 , t ) have been fixed at 3 and 1 yr, respectively. In the lower twopanels, oscillations develop with a period of 8–9 yr.

c. A numerical model to investigate the coupledoscillation mechanism
In this section we present results from two types ofidealized numerical modeling calculations. A series ofcoupled runs are carried out in which the transport of
the upper DWBC is determined by the position of the
Gulf Stream, analogous to the coupling described by
the idealized set of equations in section 8b. These results
are compared with a second set of calculations in which
the transport of the upper DWBC is specified to varyin time independent of the position of the Gulf Stream.
Our primary interest is to explore the sensitivity of
the Gulf Stream separation latitude to variations in thetransport of the upper DWBC and the coupling parameters and to determine the strength of coupling requiredin this model in order to produce large-amplitude, selfsustained oscillations. The model is very idealized andnot intended to be comprehensive. A number of processes are neglected that may be important for the variability of the Gulf Stream position and DWBC transports, including surface buoyancy forcing, temporalchanges in the wind stress, and changes in the upper
ocean component of the thermohaline circulation.

15 JULY 2000

JOYCE ET AL.

The primitive equation model described by Thompson and Schmitz (1989) is here configured with three
moving isopycal layers representing the main thermocline, an intermediate layer, and a deep layer. The model
domain extends 3000 km in longitude and 2400 km in
latitude with uniform 15-km grid resolution. The model
topography is flat everywhere except for a 250 km wideband along the western boundary where the topographyslopes uniformly from 2500 to 5000 m with slope 0.01.
Subgrid-scale mixing is parameterized through a Laplacian viscosity with mixing coefficient 200 m 2 s21 .
The resting layer thicknesses (and potential densities)
are 850 (26.25), 900 (27.75), and 3250 m (27.88).
The model is forced by a steady zonal wind stressapplied to the upper layer given by the analytic function:

tx 5

5t

2t m cos(p y/L),m{1 1 cos[p (y 2 y m )/(L 2 y m )]}/2,

y , ym ,y . ym .

The zero wind stress curl occurs at latitude y m 5 1200
km. The maximum wind stress is given by t m , which
will be varied for different experiments. This distribution gives a stronger maximum wind stress curl in thesubtropical gyre than in the subpolar gyre, crudely representing the zonally averaged zonal wind stress over
the North Atlantic.
The model is also forced through inflow/outflow
boundary conditions that represent the upper and lower
components of the DWBC. The transport is specified toflow into the model domain through a 225-km-wide
inflow port in the northwest corner. The DWBC waters
are required to exit the model domain through the southern boundary such that total mass within each layer isconserved. There is no cross-isopycnal mass flux within
the model domain. The outflow boundary conditions use
a radiation condition on the transport normal to theboundary. Details can be found in Thompson andSchmitz (1989). A similar model configuration was usedby Spall (1996a,b) to study the interaction between the
Gulf Stream and the DWBC under steady forcing conditions.
1) COUPLED RUNSThe model is initially spun up from rest for a periodof 20 yr under steady wind forcing and a fixed, specified
transport in both the upper and lower DWBC (5 Sv foreach component, 1 Sv 5 10 6 m 3 s21 ). After the 20-yr
spinup, the upper DWBC transport D is determined by
D 5 D 0 1 g(Ygs 2 Y 0),(9)where D 0 is the reference transport of the upper DWBC,
g is the change in DWBC transport induced by a lateralshift in the position of the Gulf Stream, Ygs is the timelagged position of the Gulf Stream, and Y 0 is the reference position of the Gulf Stream at the end of the
spinup period (averaged between years 15 and 20). The
position of the Gulf Stream is defined as the latitude of2563

maximum zonal velocity averaged between 65 and 450
km longitude. The general results are not sensitive tothe specific definition of the Gulf Stream position. The
outflow transport in the upper DWBC layer is the sameas the inflow transport so that there is no mass storage
within the model domain. A few calculations have been
done in which the outflow transport is held fixed at themean inflow transport while the inflow transport is allowed to vary in time, in which case there is temporary
mass storage within the model domain. The main resultspresented here were found to be not sensitive to thischoice for the outflow transport.
The time-lagged position is given by the 1-yr averageof the Gulf Stream position beginning at a time lag ofT years. The time lag in this model represents the time
it takes for any feedbacks in the Gulf Stream position
to influence the production of LSW and the time it takes
for these changes to be observed as a change in transport
in the upper DWBC at the inflow latitude of the model.
It should be noted here that there is no direct observational evidence that the transport of LSW changes inconnection with increased convective activity over the
Labrador Sea, although there is evidence of changes in
the properties of the LSW within the DWBC (Pickart
and Smethie 1998). The primary parameters to be varied
are the coupling strength g, the time lag T, and the
maximum strength of the wind stress t m .
The mean streamfunction in the upper two layers overthe final 50 yr of a 100-yr integration is shown in Fig.
13 for a coupled run with parameters t m 5 1 dyn cm22 ,g 5 0.1 Sv km21 , and T 5 5 yr. The upper layer circulation is dominated by the wind-driven subtropicaland subpolar gyres, the separated Gulf Stream, and inertial recirculation gyres to the north and south of the
Gulf Stream. The maximum Gulf Stream transport in
the upper layer is approximately 80 Sv. The Gulf Stream
separates approximately 200 km south of the zero windstress curl line as a result of interactions with the DWBC
(see also Thompson and Schmitz 1989; Spall 1996a,b).
The intermediate layer circulation is dominated by the
DWBC and the inertial recirculation gyres. The DWBC
is deflected off the western boundary where it crosses
under the Gulf Stream, splitting into mean paths flowing
eastward under the Gulf Stream and southward along
the western boundary. The dynamics of this bifurcationof the DWBC are discussed in Spall (1996a).
The location of the Gulf Stream axis as a function of
longitude (out to 1200 km) and time is shown in Fig.
14a. After the active coupling is turned on at year 20,
the Gulf Stream position oscillates with a period of approximately 11 yr. The period is close to twice the time
lag of 5 yr, slightly longer because it takes some time
for the changes in DWBC transport at the inflow to befelt at the crossover. The peak to peak variations in thelatitude of the stream are greater than 200 km. The rms
variability of the Gulf Stream separation point (definedas the average Gulf Stream latitude between 0 and 200
km longitude) is 45 km. The Gulf Stream position varies

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JOURNAL OF CLIMATEVOLUME 13

FIG. 14. (a) Deviation of the Gulf Stream axis from its mean position as a unfunction of time and longitude for the coupled run inFig. 14. Anomalies are relative to the mean between the years of 20
and 100; contour interval is 10 km with positive (negative) excursions
as solid (dashed) lines (b) upper DWBC transport as a function oftime, coupling was turned on at year 20.

FIG. 13. Mean transport streamfunction (Sv) between yr 50 and
100 for (a) the upper layer and (b) the middle layer with parameterst m 5 1 dyn cm22 , T55 yr, g 5 0.1 Sv km21 .

most strongly within 300 km of the western boundary,however coherent translations of the Gulf Stream position are found extending to greater than 1000 km into
the basin, approximately over the entire extent of themodel Gulf Stream.
The transport in the upper DWBC as a function oftime is shown in Fig. 14b. The mean over the entire
100-yr integration is 5.04 Sv, very close to the initially
specified 5 Sv. However, the amplitude of the transport
fluctuates strongly between 0 and over 10 Sv (rms variability is 2.9 Sv) with a period of approximately 11 yr.
The DWBC transport lags the Gulf Stream position suchthat the transport is maximum (minimum) approximately 5 yr after the Gulf Stream is in its northernmost(southernmost) position.
The strength of the oscillation in the Gulf Stream
position and DWBC transport depends strongly on the
coupling strength g and the time lag T. Figure 15a shows
results from a series of 100-yr calculations in which thecoupling parameter is varied while holding the time lag
fixed at 3 yr. Two sets of calculations are included, onewith t m 5 1 dyn cm22 and one with t m 5 0.75 dyn

cm22 . The natural variability of the Gulf Stream separation latitude in the absence of any active coupling isapproximately 12 km for both values of the wind stress.
The variability is not appreciably larger than the naturalvariability in the uncoupled system for weak couplingof strength g , 0.05. Oscillations much larger than thenatural variability appear only when the couplingstrength is g ø O(0.1), which corresponds to a change
of DWBC transport of 10 Sv for a lateral shift in the
Gulf Stream position of 100 km.
The variability in the separation point of the Gulf
Stream is also dependent on the time lag T in the coupling between the DWBC transport and the position of
the Gulf Stream, as shown in Fig 15b. (The period of
the oscillation is approximately twice the time lag.) Veryrapid feedback between the position of the Gulf Stream
and the transport in the DWBC reduces the variabilityof the separation point. With the strongest wind stress(t m 5 1.0), the variability in the coupled case is lessthan the natural variability in the uncoupled run. Thisis consistent with the stabilizing influence that one
would expect for zero time lag. Increased time lag results in increased variability because this allows theanomalous DWBC transport more time to cause a shift
in the separation point of the Gulf Stream before thefeedback alters the DWBC transport. Because the separation point does not continue to drift unbounded awayfrom the zero wind stress curl line for an anomalous

15 JULY 2000

2565

JOYCE ET AL.

FIG. 15. Root-mean-square variability of the Gulf Stream separation point (defined as the average
Gulf Stream position between 0 and 200 km longitude). The symbols indicate the value of the
maximum wind stress: squares for t m 5 1 dyn cm22 and stars for t m 5 0.75 dyn cm22 . (a)Sensitivity to the strength of the coupling between the Gulf Stream position and variations in
DWBC transport, g with T 5 3 yr. (b) Sensitivity to the time lag T with g 50.1 Sv km21 . (c)Variability of the separation latitude for uncoupled calculations in which the transport of the upper
DWBC is specified to vary sinusoidally with a period of 10 yr and amplitude as indicated in the
figure. (d) Variability of the Gulf Stream latitude (defined as the average latitude of the Gulf
Stream axis between the western boundary and the longitude where the maximum zonal velocity
drops below 80% of its maximum value) as a function of the variability in DWBC transport for
all coupled calculations with g $ 0.08 Sv km21 .

DWBC transport, it is expected that the variability
should level off for large T, as found here.
2) UNCOUPLED RUNSThe coupled runs indicate that a feedback between
the Gulf Stream position and the transport in the upper
DWBC can result in self-sustaining oscillations if thecoupling is sufficiently strong. A series of uncoupledexperiments has been carried out in which the transportof the upper DWBC is varied sinusoidally with specified
period and amplitude.
The variability of the Gulf Stream separation point
as a function of the variability in the upper DWBC
transport is shown in Fig 15c for a series of 100-yr
calculations in which the amplitude of the upper DWBC
transport is varied sinusoidally with a period of 10 yr.
There is a nearly linear relationship between the variability in the DWBC transport and the variability in theseparation latitude of the Gulf Stream. The rms variability in the Gulf Stream separation latitude dY s (km)may be related to the rms variability in the DWBC
transport dD (Sv) through a linear least squares fit of
the formdY s 5 a 1 bdD.

(10)

The natural variability in the separation point with asteady upper DWBC transport is a and the increase invariability of the separation point as a result of increasing variability in DWBC transport is b. A least squares
fit to the model data points gives a 5 12.5 km and b
5 7.4 km Sv21 with a standard deviation of 4.3 km,
corresponding to a nondimensionalized b 5 0.41. The
frequency of the oscillations in Gulf Stream position isdetermined by the period of the variations in DWBC
transport. The amplitude of the response to variations
in DWBC transport is only weakly dependent on thisfrequency as long as the period is several years or longer,

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JOURNAL OF CLIMATE

similar to the sensitivity to the time lag for the coupledmodel in Fig 15b. The variability decreases considerably
for variations in DWBC transport with a period of 1 yr.
These results can be used to understand the sensitivityof the oscillations in the coupled model to the strengthof the coupling parameter g. Low-frequency variationsin the DWBC transport influence the separation pointof the Gulf Stream by an amount bdD, regardless ofwhat is responsible for the change in DWBC transport.
The sensitivity of the Gulf Stream position to changes
in the DWBC transport must be sufficiently strong if
the coupled model is to produce self-sustaining oscillations that are larger than the natural variability of the
Gulf Stream. For example, if the Gulf Stream shifts byan amount dY due to its own natural variability, thecoupled model would produce a change in the DWBC
transport of gdY. The model responds to this change byshifting the separation point of the Gulf Stream by anamount bgdY. If bg K 1, then the resulting shift of the
Gulf Stream will not return it to its original latitude andthe oscillation amplitude will be smaller than the uncoupled variability. If bg ø 1, then the Gulf Stream
will shift back to its original position and the oscillation
will be comparable to the uncoupled variability. For bg
k 1 the coupled oscillation becomes larger than theoriginal perturbation and it will grow to dominate thevariability. This is consistent with the rapid increase invariability of the coupled system near g 5 0.1, where
bg 5 0.74.
Variations in the Gulf Stream separation point would
most strongly influence the atmosphere if the latitudeof the Gulf Stream were also impacted far from theseparation point, as in Fig. 6. Although the variability
in Gulf Stream position is strongest near the westernboundary of the model, Fig. 13 clearly shows that there
is a penetration of this signal far into the ocean interior.
The Gulf Stream latitude is defined as the average latitude of the Gulf Stream axis over the entire penetration
distance of the Gulf Stream. The penetration scale isdefined here to be the longitude where the zonal velocity
drops below 80% of its maximum value. For the calculation in Fig. 13, the average penetration scale is 960
km. The penetration scale varies between 400 and 1100
km over all of the calculations. The dependence of the
Gulf Stream latitude on the variability in the upper
DWBC transport is shown in Fig. 15d for all coupledmodel runs with g $ 0.08. The trend of increasing variability in Gulf Stream position with increasing variability in upper DWBC transport is retained over theentire zonal length scale of the Gulf Stream. This isfound for both the coupled and uncoupled runs. A leastsquares fit results in a 5 10.4 km and b 5 8.2 km Sv21
with a standard deviation of 13.7 km. The slope of theleast square fit line is partly determined by the choiceof coupling parameter as b ø g21 . There is a slightdifference because the diagnosed position of the Gulf
Stream used to determine the DWBC transport is dif-

VOLUME 13

ferent from the average position over the entire penetration scale of the Gulf Stream.
The simple model formulation used here identifies
several important features of the midlatitude oceanic
response to low-frequency variability in the thermohaline circulation. First, we have demonstrated that the
Gulf Stream changes latitude in response to low-frequency variations in the DWBC transport. The magnitude of this variability in the model is consistent withthe observed variability in Gulf Stream position between
the pentads discussed earlier (approximately 50–100km) and variability of DWBC of O(5 Sv). This response
also quantifies the approximate ‘‘coupling’’ strength between shifts in the Gulf Stream position and deep western boundary transport that would be required in orderfor the system to support self-sustaining oscillations.
Finally, the model calculations also showed that the interactions between the Gulf Stream and the DWBC near
the separation point cause a large-scale (approximately
1000 km) coherent shift in the Gulf Stream latitude wellinto the basin interior. This is also consistent with thelongitude over which the Gulf Stream was found to shift
position in Fig. 6.
9. Summary
We briefly summarize the findings of our work as alist of major results using data from the years 1954–89
inclusive.
R Interannual variability of the STMW potential vorticity is correlated with atmospheric buoyancy forcing
and in phase as if the ocean were passively driven
with eddies doing the damping.
R Associated with this STMW variability, the largescale atmospheric SLP signal resembles the spatial
pattern of the NAO and an NAO index is correlated
in time with STMW PV with no temporal phase lag
between the two.
R Gulf Stream position also shifts interannually with the
STMW/NAO and the maximum correlation occurs atzero phase lag between the GS/NAO/STMW PV, although the GS is as highly correlated with the NAO
at a lag of 1 yr as at 0 lag.
R Pentadal analysis of climatological extremes of
STMW PV show north–south shifts in the GS position, the latitude of the zero wind stress curl, and theextratropical winter storm tracks.
R If GS position can affect the air–sea exchange, thena feedback loop can be established in which the control of GS position by the DWBC transport at thecrossover point produces decadal oscillations of the
GS and the air–sea fluxes controlling both the source
waters of the DWBC in the Labrador Sea and the
STMW in the Sargasso Sea.
R Model calculations suggest that this feedback mechanism is capable of creating self-sustaining oscillations only if the degree of coupling between GS lat-

15 JULY 2000

JOYCE ET AL.

2567

itude and LSW transport variability is moderately robust.
Our model results have demonstrated necessary, but
not sufficient, conditions for such an active coupling
between the ocean and atmosphere. While the sensitivity
found in the model is consistent with the observed variability, we can not conclude that there must be an active
feedback through the atmosphere. It is possible that the
low-frequency variability in both the Gulf Stream andthe formation of LSW are being forced by the atmosphere independent of each other. It is also possible thatthe observed variability in Gulf Stream position is aconsequence of low-frequency variability in the strengthof the thermohaline circulation, but that the resultant
changes in SST have no discernable effect on the position of atmospheric storm tracks. While it is beyond
the scope of the present study to resolve these issues,
we feel that the present results provide useful insight
into the midlatitude oceanic response to low-frequency
variability in the thermohaline circulation and hope thatthey will stimulate further research into possible midlatitude coupling mechanisms.
We recognize that the NAO system is more complicated than our simple model assumes (low salinity
anomalies capping the Labrador Sea, for example) andadmit that our assumption of a strong atmospheric coupling to Gulf Stream SST anomalies is speculative. It
is also clear from our findings that the shortness of therecord and the long timescale of the variability limits
the statistical confidence which can be brought to bear.
Work is currently underway to extend our analyses another decade within the next year using data from the
1990s.

FIG. A1. The GS index used in this study (solid curve) comparedwith two versions of the GS index based on data from A. H. Taylor(1999, personal communication; long and short dashed curves) for amore recent time period (1966 or 1975–98). The Taylor indices are
based on annual mean data for the full time period (GS t1 ) and forthe post-1974 time period (GS t2 ).

time interval is different. Because we contend that thefirst years of the Taylor estimate are different from ours,
we have updated our Gulf Stream (and NAO) estimates
through 1998 to overlap with the Taylor frontal analysis
data. We have analyzed the T(200 m) and frontal analysis datasets similarly, using the covariance matrix (notcorrelation matrix) for our comparisons. In our previ-

Acknowledgments. This work is part of the WOCE
effort within the Atlantic Circulation and Climate Experiment, and is supported by NSF Grants OCE9529607 (TJ), OCE95-31870 (CD), and OCE95-31874(MS). Thanks go to J. Dunworth-Baker and R. Goldsmith who helped with some of the various data extractions, for assistance from M. Timlin using theGrADs software package, and to C. Frankignoul, forseveral discussions. A. Taylor provided some unpublished data as well as comments, with another anonymous reviewer, on an early draft of this manuscript.
APPENDIX
Comparison of Two Different Indices of Gulf
Stream Position
In order to address the reasons why our results onmean Gulf Stream position and its correlation with the
NAO differ from those published by Taylor and Stephens, Taylor provided us with his annual mean Gulf
Stream data from longitudes 798, 758, 728, 708, 678, and658W for the period 1966–98, inclusive. Note that theseare different positions than we have used and that the

FIG. A2. Lagged cross correlations between the NAO and the GS
indices shown in Fig. A1. The lag correlation between the GS index
used in this study and that based on data from Taylor for the period
1975–98 (thin solid curve) indicates the two to be correlated with notime lag.

2568

JOURNAL OF CLIMATE

ously described work above, we have felt that the covariance method, which gives more weight to the moreenergetic longitudes, is more appropriate since that iswhat the atmosphere sees. We have made two different
estimates from the Taylor data: one using the wholedataset and the other excluding data before 1973. The
results are shown in Fig. A1 for the leading EOFs, which
typically contain about 50% of the variance in the covariance matrices. We have further compared the lagged
correlation of the various time series (including an updated, smoothed NAO) in Fig. A2.
First of all, we can see the discrepancy between Taylor’s 1966–98 leading EOF and ours, which is based on
98 longitudes between 758 and 558W. The overlapping
two time series of the Taylor estimate with and without
the pre-1975 data are slightly different because of thedifferent longitudinal loading in the EOFs. It is clearthat our GS estimate and that of Taylor’s shorter estimate
are both most highly correlated with the NAO at 0- and1-yr lags, with the maximum correlation now at 1-yr
lag compared to 0- and 1-yr lags when the period 1955–
89 is used (recall Fig. 8). The longer Taylor record
exhibits maximum correlation with the NAO at lags 1–3
yr; however, we maintain that this is due to some peculiarities of the frontal analysis data in the initial years
that we cannot explain.
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