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Observed Interannual Variability of the Florida Current: Wind Forcing and the
North Atlantic Oscillation
PEDRO N. DINEZIO AND LEWIS J. GRAMER
Cooperative Institute for Marine and Atmospheric Studies, Rosenstiel School of Marine and Atmospheric Science,
University of Miami, Miami, Florida
WILLIAM E. JOHNS
Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida
CHRISTOPHER S. MEINEN AND MOLLY O. BARINGER
Physical Oceanography Division, NOAA/Atlantic Oceanographic and Meteorological Laboratory, Miami, Florida
(Manuscript received 14 February 2008, in final form 5 September 2008)
ABSTRACT
The role of wind stress curl (WSC) forcing in the observed interannual variability of the Florida Current
(FC) transport is investigated. Evidence is provided for baroclinic adjustment as a physical mechanism
linking interannual changes in WSC forcing and changes in the circulation of the North Atlantic subtropical
gyre. A continuous monthly time series of FC transport is constructed using daily transports estimated from
undersea telephone cables near 278N in the Straits of Florida. This 25-yr-long time series is linearly regressed
against interannual WSC variability derived from the NCEP–NCAR reanalysis. The results indicate that a
substantial fraction of the FC transport variability at 3–12-yr periods is explained by low-frequency WSC
variations. A lagged regression analysis is performed to explore hypothetical adjustment times of the wind-
driven circulation. The estimated lag times are at least 2 times faster than those predicted by linear beta-plane
planetary wave theory. Possible reasons for this discrepancy are discussed within the context of recent
observational and theoretical developments. The results are then linked with earlier findings of a low-
frequency anticorrelation between FC transport and the North Atlantic Oscillation (NAO) index, showing
that this relationship could result from the positive (negative) WSC anomalies that develop between 208and
308N in the western North Atlantic during high (low) NAO phases. Ultimately, the observed role of wind
forcing on the interannual variability of the FC could represent a benchmark for current efforts to monitor
and predict the North Atlantic circulation.
1. Introduction
The Florida Current (FC), the name commonly used
for the Gulf Stream where it flows through the Straits of
Florida, is a component of the western boundary current
system of the North Atlantic subtropical gyre. In addi-
tion to being a component of the wind-driven gyre, it is
also a pathway for the warm-water return flow of the
global meridional overturning circulation (MOC). Over
the past 25 yr, electromagnetically induced voltages on
several undersea telephone cables near 278N have been
successfully used to produce daily estimates of the total
volume transport of seawater through the Straits of
Florida (Larsen and Sanford 1985; Baringer and Larsen
2001).
This cable record has been used to study seasonal
variations in FC transport along with sea level differ-
ences and direct ocean current measurements (Schott
and Zantopp 1985; Molinari et al. 1985; Lee et al. 1985;
Larsen and Sanford 1985; Baringer and Larsen 2001;
Hamilton et al. 2005). The relationship between these
seasonal changes and variations in wind forcing over the
North Atlantic has been extensively studied (Schott and
Zantopp 1985; Lee et al. 1985; Lee and Williams 1988).
Most observational studies agree with the model results
Corresponding author address: Pedro N. DiNezio, CIMAS,
RSMAS, University of Miami, 4600 Rickenbacker Causeway,
Miami, FL 33149.
E-mail: pdinezio@rsmas.miami.edu
MARCH 2009 D I N E Z I O E T A L . 721
DOI: 10.1175/2008JPO4001.1
of Anderson and Corry (1985a,b), Fanning et al. (1994),
and Greatbatch et al. (1995), identifying local and re-
mote along-isobath wind stress forcing as a driving
mechanism for annual and higher-frequency variability,
while modeling studies by Bo
¨ning et al. (1991) point
to wind stress curl (WSC) variability over the western
North Atlantic.
Significant interannual variability has also been
inferred from sea level differences (Schott and Zantopp
1985) and from the cable-derived transport estimates
(Baringer and Larsen 2001). Using 16 years of data,
Baringer and Larsen report peak-to-peak interannual
variations of 2–3 Sv (1 Sv [10
6
m
3
s
21
) having periods
between 2 and 3 yr and an apparent longer decadal-
period variation of62 Sv .T he interannual estimate agrees
with those previously derived by Schott and Zantopp for
the same frequency band, using approximately 8 yr of sea
level differences between Bimini and Miami.
Suggestion has been made in the literature of a rela-
tionship between variations in FC transport and inter-
annual and longer-period atmospheric signals. Baringer
and Larsen (2001) compared a 2-yr running mean of FC
cable transport with variations in the North Atlantic
Oscillation (NAO) index over the period 1982–96. Al-
though their analysis spanned fewer than two complete
cycles of a 10–12-yr mode, also present in the low-
frequency variability of both the FC and the NAO, they
did identify a strong anticorrelation between the two
signals at shorter interannual periods. The NAO index
is a measure of broad atmospheric variability over the
North Atlantic, based on differences in sea level at-
mospheric pressure at long-term monitoring stations in
Iceland and the Azores (Hurrell and van Loon 1997).
Changes in the NAO index are associated with changes
in the strength of the westerly winds over the North
Atlantic, with a high NAO corresponding to stronger
westerlies and enhanced negative WSC over the mid-
latitude North Atlantic. Baringer and Larsen found a
lag of 18 months between anomalies in the NAO index
and FC transport anomalies of opposite sign, but the
physical mechanism for this observed relationship has
not heretofore been established.
On interannual time scales, theoretical (Anderson
and Gill 1975) and model studies (Anderson et al. 1979)
indicate that adjustment of the North Atlantic sub-
tropical gyre to changes in atmospheric forcing over the
basin is achieved by the propagation of long-limit
(nondispersive) barotropic and baroclinic Rossby waves
adjusting the Sverdrup circulation in their wake. Ulti-
mately, only the baroclinic Rossby waves could transmit
this signal to the Straits of Florida through the topog-
raphy of the Bahamas. This assumption is supported by
studies using quasigeostrophic two-layer models (e.g.,
Pedlosky and Spall 1999; Pedlosky 2000) showing that
westward-propagating energy associated with baroclinic
Rossby waves can be radiated westward by small gaps in
a topographic barrier, thus making this idealized island
arc transparent to the waves. While the spinup theory of
Anderson and Gill (1975) focused on first-mode baro-
clinic Rossby waves excited by WSC forcing along the
eastern boundary, subsequent studies using numerical
models have shown that free Rossby waves can also be
generated in the ocean interior by wind forcing, for
example, over an ocean ridge (Barnier 1988), or they
can be directly forced by the wind over open ocean
(White 1977; White et al. 1998; Qiu et al. 1997). These
results are consistent with recent satellite altimeter ob-
servations indicating significant generation of both bar-
otropic and baroclinic Rossby waves in the ocean inte-
rior, sometimes correlated with major topographic fea-
tures (Chelton and Schlax 1996, hereafter CS96).
The present study analyzes monthly mean WSC data
over the 278N latitude band across the subtropical North
Atlantic to show a relationship between WSC and FC
transport variability with periods in the range between 2
and 12 years, the longest time scale that can be studied
with the cable data available to date. It is demonstrated
that FC fluctuations on these time scales are consistent
with a lagged adjustment of the subtropical gyre to in-
terior WSC anomalies associated with the NAO. While
such a relationship is not unexpected, our analysis shows
that the connection between the FC and the NAO is a
rather subtle one, in which WSC anomalies near 208–
308N that are opposite in sign to those in the main center
of action of the NAO could actually be driving the re-
sponse. The analysis further suggests that the response
time of the gyre to these WSC anomalies is significantly
faster than predicted by conventional planetary wave
theory but consistent with recent observations and
theoretical developments.
The paper is organized as follows. First, we describe
the FC cable transport time series and procedures used
for gap filling and filtering. Next, we analyze the Na-
tional Centers for Environmental Prediction–National
Center for Atmospheric Research (NCEP–NCAR)
reanalysis wind stress data over the North Atlantic for
1982–2007, illustrating the WSC pattern associated with
the NAO focusing on the zonal band of the cable mea-
surements (248–298N). Sverdrup transport signals origi-
nating in the western, central, and eastern parts of the
gyre are identified. Then, wavelet and lagged regression
analyses are performed to explore the relationship
of these forcing anomalies to the FC transport. Finally,
we conclude with a discussion of the observed coher-
ences with regard to Sverdrup balance and adjustment
times.
722 JOURNAL OF PHYSICAL OCEANOGRAPHY VOLUME 39
2. Data and methods
a. Florida Current transport time series
Using a methodology outlined by Stommel (Stommel
1948) and successfully implemented by Sanford and
Larsen (Sanford 1982; Larsen and Sanford 1985; Mayer
and Larsen 1986; Larsen 1992), several telephone cables
lying beneath the sea floor have been used to estimate
the transport of seawater through the Straits of Florida.
Our study uses approximately 25 yr of daily estimates
of volume transport derived from voltages recorded
on a series of cables near 278N (available online at
www.aoml.noaa.gov/phod/floridacurrent) to construct a
monthly FC transport time series (Fig. 1a). Over the
past 25 yr, the in situ transport observations have been
variously computed from velocity sections collected
from acoustic Pegasus velocity profilers (Mayer and
Larsen 1986) and later using a simpler free-falling drop-
sonde (Richardson and Schmitz 1965; C. Meinen, M. O.
Baringer, and R. F. Garcia 2008, unpublished manu-
script). The root-mean-square (RMS) difference between
concurrent daily estimates is less than 3 Sv. The resulting
cable time series contains occasional gaps in the record
as a result of instrument failures and funding vagaries;
the largest gap occurred between 1998 and 2000, when
funding for the project was cut at the same time the
recoding equipment needed to be removed while the
cable was decommissioned. The second longest gap
occurred in September to October 2004 when Hurri-
canes Frances and Jeanne destroyed the building in
which the recording system was housed.
Our analysis herein is based on monthly means
computed for months with at least 15 days of daily data.
Owing to the high-frequency (short integral time scale)
nature of the dominant variability, the estimated un-
certainty of the monthly mean estimates is on the order
of 1 Sv. After this procedure, eleven 1–3-month gaps
remain, along with a single 20-month gap in 1998–2000.
To analyze the full period between 1982 and 2007, the
following methodology is used to fill each gap depend-
ing on its length in months. All gaps of 3-months du-
ration or fewer are linearly interpolated. The remaining
20-month gap is then reconstructed using a climato-
logical annual cycle calculated based on the 1983–2006
record, with a linear trend added to match the data in
the years immediately before and after the gap. During
the 20-month gap, 11 daily snapshots of transport esti-
mates were obtained by the Florida Current Project
using dropsonde casts with a mean transport of 30.7 Sv,
and a standard deviation of 3.0 Sv. Moreover, satellite-
derived interannual anomalies of the sea level differ-
ence across the Straits of Florida—a proxy for geo-
strophic transport—show the two large cycles during
the 1990s and 2000s, with a smooth transition from the
1998 high to the 2000 low (G. Goni 2008, personal
communication). These two independent sets of ob-
servations support the interpolation of the gap using a
linear trend solely to produce a continuous signal for
filtering.
Prior to any filtering or statistical analyses, the mean
1982–2007 transport of 32 Sv is removed from the fully
reconstructed monthly time series. Interannual varia-
tions are then examined using bandpass filters in both
the 2–12-yr before present (YBP) and 3–12-yr (3–12
YBP) bands (Fig. 1b) to allow us to test the sensitivity of
the results to the filter period. Throughout this study,
fifth-order Butterworth bandpass filters are applied with
no phase shifting in the time domain (We elect to use
period rather than frequency throughout the paper to
clarify for the reader the time intervals being discussed).
Spurious edge effects are avoided by removing half of
the low-pass period at both ends of the filtered time
series. For reasons to be discussed later, the 3–12 YBP
filtered series is the one we will focus on in comparisons
with the WSC signals.
It should be noted that several other techniques for
completing the monthly FC transport record were eval-
uated in this study, including simple linear interpolation
of all gaps, or filling the 20-month gap using climato-
logical annual cycles corresponding to other subsections
of the cable record. However, after bandpass filtering,
the FC transport time series resulting from the different
gap-filling methodologies are found to be indistinguish-
able (figure not shown). Data from the 20-month gap
are excluded from all statistical relationships stated in
this paper. Thus, the main results presented in this paper
are insensitive to the specific method used to fill the gaps
in the FC transport time series.
b. Wind stress and WSC
Surface wind stress fields from the NCEP–NCAR
reanalysis project (Kalnay et al. 1996) are used to explore
the role of wind forcing in the interannual variability of
the FC. Monthly mean estimates of the zonal (t
x
)and
meridional (t
y
) wind stress on a T62 Gaussian grid (ap-
proximately 28328resolution) are used to estimate the
vertical component of the curl of the surface wind stress,
($3t)z, hereinafter WSC. The 1982–2007 mean cli-
matological WSC (Fig. 2) shows a region of negative
values over most of the subtropical North Atlantic, which
contributes to the long-term mean of the wind-driven
component of the FC through linear vorticity dynamics
(i.e., Sverdrup balance). This mean WSC produces a
Sverdrup transport of approximately 18 Sv at 278N. Us-
ing water mass analysis, Schmitz and Richardson (1991)
MARCH 2009 D I N E Z I O E T A L . 723
have shown that the subtropical gyre wind-driven circu-
lation accounts for about 17 Sv of the total transport of
the Florida Current at 258N, with a remaining 13 Sv
identified as water of South Atlantic origin carried by the
MOC to the Straits of Florida. Although the validity of
Sverdrup balance in the long-term mean gyre dynamics is
still a subject of controversy (e.g., Leetmaa et al. 1977;
Wunsch and Roemmich 1985; Bryan et al. 1995; Hogg
and Johns 1995), there is clear evidence from modeling
and observational studies to support an important role
for low-frequency WSC changes in the gyre circulation
(Sturges and Hong 1995; Sturges et al. 1998; Hong et al.
2000).
Three WSC forcing regions are defined over the 278N
latitude band corresponding to the latitude of the tele-
phone cable across the Straits of Florida. This latitude
band was chosen according to the physical mechanisms
hypothesized to influence the FC transport on interan-
nual scales, as discussed in the introduction. These re-
gions are designated western Northern Atlantic (WNA),
central North Atlantic (CNA), and eastern North At-
lantic (ENA), as shown from left to right in Fig. 2. Time
series of spatially averaged WSC over each region are
computed.
Several filter cutoff periods have been evaluated to
isolate the low-frequency variability of these WSC time
series and to test the sensitivity of the results to the filter
periods. Analysis of the spectra of the western and
central regions (Fig. 3a) shows a white spectral distri-
bution but with sharp annual and semiannual peaks,
consistent with previous results (e.g., Willebrand 1978).
Broader plateaus of spectral density are observed at
longer periods (lower frequencies) than the annual cy-
cle, accounting for about 10% of the variance. The sig-
nificant energy in the interannual portion of the spec-
trum for the western region is separated from the annual
and semiannual peaks by an apparent spectral gap at
periods of approximately 2 yr, but no such clear sepa-
ration occurs in the spectra for the central and eastern
regions. Signals resulting from lagged composition of
the three WSC signals show a relatively redder spec-
trum, as expected from an integration process, with
FIG. 1. (a) Monthly estimates (solid line) of FC volume transport computed from daily cable
observations (thin line) using the technique described in the text. The black dots correspond to
transport estimates obtained using dropsonde sections. (b) Filtered time series of interannual
FC transport anomalies. The solid line represents the 3–12-yr (3–12 YBP) bandpass-filtered
signal, while the dashed line shows the 2–12-yr (2–12 YBP) bandpass. Sections of the time series
subject to filtering edge effects are not shown. The 20-month gap in the cable observations
appears in gray, indicating the portion of the time series that has been interpolated, solely to
produce a continuous signal for filtering.
724 JOURNAL OF PHYSICAL OCEANOGRAPHY VOLUME 39
damped annual and semiannual peaks and clearer cut-
offs between 2- and 3-yr periods (figure not shown).
Spectral analysis of the FC time series (Fig. 3b) shows
a red spectrum consistent with the multiplicity of physical
processes operating on the FC at time scales from sea-
sonal to decadal. Less pronounced annual and semian-
nual peaks are also present in comparison with the WSC
signals. The interannual portion of the spectrum is
separated from the annual peak by a minimum at about
the 2-yr period, and the energy in this portion of the
spectrum explains about 20% of the total variance.
These results suggest the use of a low-pass cutoff at the
FIG. 2. Climatological mean surface wind stress from the NCEP–NCAR reanalysis project
between 1982 and 2007. Arrows show the wind stress field, and the contour map is the vertical
component of WSC. The WSC contours are in units of 10
27
Pa m
21
. White (gray) background is
for positive (negative) mean WSC. Three regions are outlined across a latitude band centered at
278N, corresponding approximately to the Straits of Florida: WNA, CNA, and ENA. WSC
forcing over these regions is hypothesized to influence the FC transport on interannual time
scales, via baroclinic adjustment. The solid line shown following continental coastlines corre-
sponds to the 200-m isobath.
FIG. 3. (a) Spectra of the WSC time series for each forcing region. The lines correspond to
regions: solid black is western; solid gray is central; and dashed gray is eastern. (b) Spectrum
of the Florida Current transport time series. The time series are normalized to zero mean and
unit variance before computing the power spectral density (PSD), resulting in dimensionless
values of PSD. The frequency axis is in cycles per year, with 108corresponding to the annual
frequency.
MARCH 2009 D I N E Z I O E T A L . 725
3-yr period. Ultimately, this choice is best illustrated by
a time-dependent cross-spectral analysis between the
composite WSC signal and FC transport like that pre-
sented in the results section, where variability at the 3-yr
and longer periods show a distinct separation. Addi-
tionally, a 12-yr high-pass cutoff has also been applied to
the WSC forcing signal to remove decadal- and longer-
period modes, which would not be well resolved by the
approximately 25-yr-long FC record.
The NAO index used in this analysis is based on the
periodically updated data distributed by the National
Oceanic and Atmospheric Administration’s Climate
Prediction Center (available online at http://www.cpc.
noaa.gov/data/teledoc/nao.shtml). This monthly index
is derived following the methodology of Barnston and
Livezey (1987), based on a rotated principal component
analysis that isolates the primary teleconnection pat-
terns of the NAO using year-round data rather than just
winter data.
The resulting low-frequency WSC signals for each of
the forcing regions (Figs. 4a–4c) all have amplitudes of
order 10
28
Pa m
21
, which are about 15% of the monthly
signal amplitude (order of 10
27
Pa m
21
) associated with
the annual or semiannual peaks. Moreover, a visual cor-
respondence with low-frequency NAO index variability
(Fig. 4d) can be observed, especially for the western and
central regions. This suggestion of a positive relation-
ship between the NAO and the WSC field over the
latitude band of the Straits of Florida is further explored
in the next section using a regression analysis of the
wind fields and the low-frequency NAO index.
3. Results
a. WSC forcing associated with NAO interannual
variability
Since the NAO is a major mode of interannual at-
mospheric variability over the North Atlantic, we ex-
amine low-frequency covariability between the NAO
and the wind field over the forcing regions at 278N. We
linearly regress the monthly wind stress components
and their associated curl onto the 3–12 YBP filtered
NAO index. Regression coefficients that are significant
with 67% probability are considered. Using this proce-
dure, a pattern of NAO–WSC interannual covariability
emerges (Fig. 5), where a high NAO index is associated
with positive anomalies in WSC over the western and
central portions of the forcing region along 278N.
A high NAO index is generally associated with a
strengthening of both westerly and trade winds, akin to a
strengthening of the mean wind field over the North
Atlantic (Fig. 2), which simple intuition might associate
with a negative WSC forcing anomaly. Our result, in
fact, demonstrates the opposite, showing that a positive
WSC anomaly over the latitude band of the Straits of
Florida is produced by a band of negative anomalies in
the westerlies between about 308and 408N (cf. Figs. 5
and 2). These zonal wind anomalies arise from a basin-
wide anticyclonic atmospheric circulation within the
center of action of the NAO near 408–508N. The re-
gression further indicates that WSC anomalies associ-
ated with low-frequency variability of the NAO, ap-
proximately 0.5 310
28
Pa m
21
in the western and
central regions, have the same order of magnitude as the
interannual WSC anomalies that are actually observed
in the NCEP–NCAR data (10
28
Pa m
21
; Figs. 4b and
4c). Additionally, the correlation coefficients associated
with the WSC–NAO regressions are found to be signif-
icant at the 67% level over the latitude band hypothe-
sized to influence the Florida Current (Fig. 5b), indi-
cating that a substantial fraction of the interannual var-
iability of the WSC over this region can be linked with
the NAO.
The ocean response to the anomalous anticyclonic
atmospheric circulation associated with high NAO has
been extensively studied, for example, by Eden and
Willebrand (2001) and Marshall et al. (2001), focusing
on the intergyre dynamics near the subpolar front. This
pattern of anomalous easterlies north of the latitude
band of the Florida Straits, with positive WSC at about
308N, can be recognized in previous studies of the NAO
(e.g., Eden and Willebrand 2001; Marshall et al. 2001;
Visbeck et al. 2003), yet no links with the Florida Cur-
rent or with adjustment processes in the subtropical
gyre circulation have been proposed. Adjustment of the
Sverdrup transport in the North Atlantic subtropical
gyre to this positive WSC anomaly should drive a neg-
ative anomaly in the FC transport. Thus, the observed
WSC–NAO interannual covariability can associate a
high NAO index with negative FC transport anomalies,
provided that an adjustment process links the gyre-wide
WSC forcing with the western boundary current system.
Evidence for such a link could, therefore, explain the
observed anticorrelation between the NAO index and
the cable-derived FC transport time series on interan-
nual time scales (e.g., Baringer and Larsen 2001).
b. Composition of forcing signals based on baroclinic
adjustment
The WSC forcing time series computed for each of the
three regions in the latitude band of the Straits of
Florida are individually lagged in time and then com-
bined. Composite forcing time series are used to evalu-
ate the potential role of baroclinic adjustment in the low-
frequency adjustment of the North Atlantic subtropical
726 JOURNAL OF PHYSICAL OCEANOGRAPHY VOLUME 39
gyre. Adjustment times associated with the long limit of
linear first baroclinic-mode Rossby waves are initially
considered. These adjustment times are estimated from
the center of each forcing region, based on group
propagation speeds obtained by Sturges et al. (1998) using
hydrography and standard beta-plane theory. The ad-
justment times are based on simple linear first baroclinic-
mode group speeds, derived on a beta plane for an
ocean at rest with a flat bottom. Consequently, all po-
tential effects on the adjustment times due to higher
baroclinic modes, topography, the full sphericity of the
earth’s surface, or mean flow are neglected.
The time series of WSC anomaly within each of the
three regions are first converted into equivalent
Sverdrup transport anomalies and then shifted in time
according to the lags specified in Table 1. The Sverdrup
integral along 278N (i.e., the gyre-wide Sverdrup trans-
port) is computed as the sum of the lagged Sverdrup
transport signals corresponding to the three regions con-
sidered. This approximation of the integral as a sum-
mation of three spatial averages is valid as a result of the
autocorrelation remaining in the filtered signals and
the spatial coherence of the low-frequency forcing. For
the Sverdrup scaling, we choose a planetary vorticity
gradient b52310
211
m
21
s
21
corresponding to 278N,
a seawater reference density r
0
510
3
kg m
23
, and a
zonal extent for each forcing region (Fig. 2) of L523
10
6
m. According to the Sverdrup balance (Sverdrup
1947), the volume transport associated with a WSC
anomaly of 10
28
Pa m
21
is
FIG. 4. Time series of WSC from each of the three forcing regions: (a) eastern, (b) central,
and (c) western. (d) Time series of NAO index. In each figure, light gray lines are the original
unfiltered monthly time series, solid lines are the 3–12 YBP filtered signals, and dashed lines are
the 2–12 YBP filtered signals. Note that all four vertical axes are inverted for ease of com-
parison with the FC signal in Fig. 6.
MARCH 2009 D I N E Z I O E T A L . 727
The amplitude of the resulting transport signal is
between 2 and 3 Sv (Figs. 6b and 6c), consistent with
observed interannual anomalies in FC transport of 3 Sv
or less, as shown by the 3–12 YBP filtered time series
(Figs. 1b or (6a) and as found by Baringer and Larsen
(2001). Note that the signals have opposite signs, since
northward anomalies in interior Sverdrup transport
lead to southward anomalies in FC transport. Thus, the
observed magnitude of interannual WSC anomalies
over this latitude band would be sufficient to explain
FIG. 5. (a) Wind stress (arrows) and WSC (contours), resulting from a regression of the
NCEP–NCAR reanalysis onto a 3–12 YBP filtered time series of the NAO index. The WSC
contours are in units of 10–8 Pa m
21
. White (gray) background shows areas of positive (neg-
ative) regressed WSC anomaly. A heavy dashed contour outlines areas where the NAO–WSC
regression is distinct from the null hypothesis (Student’s ttest) with 67% confidence. Note that
this area encompasses much of the center of action of the NAO and the entire western and
central portions of the 278N latitude band. (b) Correlation coefficient corresponding to the
regression results shown in (a). The dashed contour outlines areas where the NAO index–WSC
coherence is distinct from the null hypothesis (chi squared).
transport ;(WSC)L
r0b
ffi(108kg m2s2)(2 3106m)
(103kg m3)(2 31011 m1s1)5106m3s1deg 1 Sv.
728 JOURNAL OF PHYSICAL OCEANOGRAPHY VOLUME 39
observed interannual FC transport anomalies, assuming
the two signals are found to be coherent. Some degree
of correspondence can be observed between the com-
posite forcing signal (Fig. 6c) and the FC signal (Fig. 6a).
However, the composite forcing signal has the appear-
ance of leading the FC fluctuations, even though it has
been lagged using linear Rossby wave group speeds.
Alternatively, when adjustment times of just 40%
(hereinafter 0.4X) of the standard theory are used (Fig.
6b), the composite WSC-driven signal is not only more
clearly in phase with FC transport but also appears to be
in phase with the NAO signal (Fig. 6d). The correlation
coefficient rbetween the 0.4X-adjusted WSC forcing
and the 3–12 YBP signals of the FC and NAO is 20.72
and 0.69, respectively, and is 20.71 between the 3–12
YBP FC and NAO signals (These correlations exclude
the 20-month gap in the FC time series, as do all sta-
tistical results in this study). Thus, using the faster ad-
justment times, while implying propagation speeds
about twice as fast as classical beta-plane theory, leads
to a stronger coherence and increased consistency with
the observed NAO–FC relationship. The sensitivity of
the coherence and scaling between the WSC forcing and
FC transport signals to different assumed adjustment
times is explored more carefully in section 3c.
The spatial distribution of the apparent gyre adjust-
ment times can be further investigated by estimating the
lags corresponding to the peak coherence (maximum
negative regression slope) between interannual WSC
forcing variability and FC transport for each ;28328
grid point in the NCEP–NCAR dataset (Fig. 7b). The
western and central regions show the highest peak re-
gression values, while the optimal lags (Fig. 7a) show an
increase toward the east in the subtropical North Atlan-
tic, consistent with a westward-propagating adjustment
process, such as planetary waves. Again, these adjustment
times imply Rossby wave energy propagating with speeds
ranging between 2 and 3 times the theoretical values.
In the CNA and WNA regions in Fig. 7b, the esti-
mated lag times imply much faster Rossby wave prop-
agation compared to the 13- and 35-month theoretical
adjustment times for these regions given in Table 1.
Conversely, a portion of the ENA region shows implied
adjustment times longer than 35 months, more consis-
tent with the 55-month lag given for this region in Table
1. Finally, the mean correlation coefficient for each
forcing region (Fig. 8) shows that the western and cen-
tral forcing regions are more coherent (r.0.6) with the
FC time series compared with the eastern region (r,
0.4). The estimated lag times for these optimal corre-
lation coefficients are 6 64 months for the western re-
gion, 7 65 months for the central region, and 20 69
months for the eastern region.
c. Regression of WSC and FC transport interannual
variability
When the standard adjustment times are used (Figs. 6a
and 6c), the magnitude of the signals’ coherence is 20.2,
and the regression coefficient fails the null hypothesis
test. Conversely, statistical significance (at 67% level)
is achieved when lag times that are 40% of the theo-
retical values are used (Fig. 6b), with correlation coeffi-
cients of 20.66 and 20.72 for the 2–12- and the 3–12
YBP filtered signals, respectively. To explore the co-
herence between the FC and WSC signals over a range
of possible adjustment lags, multipliers from 20.5 to 1.5
times the theoretical beta-plane adjustment times are
considered, and the sensitivity of the FC response to
this one-dimensional parameter (lag multiplier) is ex-
amined.
Figure 9 summarize the sensitivity of the FC–WSC
linear regression to both the assumed adjustment lag
times and the bandpass filtering applied. The regression
coefficient corresponds to the slope (or gain) of the least
squares best-fit line between the filtered time series of
lagged Sverdrup transport forced by the WSC and the
FC transport. A regression coefficient of 1.0 would in-
dicate that the low-frequency variability in Sverdrup
transport and observed FC transport are consistent,
while a high-correlation coefficient simply indicates a
high coherence between the signals, without reference
to their scaling. The time series are subsampled to re-
flect a reduction in effective degrees of freedom (DOF)
consistent with 2- and 3-yr integral time scales identified
in the autocorrelation function of the regression resid-
uals for each cutoff band. The resulting equivalent
DOFs for the two cutoff periods are 11 and 7, respec-
tively, after edge effects are removed.
TABLE 1. Wave group speeds and hypothetical adjustment times for changes in WSC over each of the three WSC forcing regions
corresponding to the 278N latitude band, computed using hydrographic observations and standard beta-plane theory by Sturges et al.
(1998).
Region Lat (8N) Lon (8W) Adjustment speed c
g
(cm s
21
)
Mean distance to Straits
of Florida d(km)
Adjustment time dc
g
21
(months)
WNA 238–298758–5584 1400 13
CNA 238–298558–3583.8 3500 35
ENA 238–298358–1583.5 5200 55
MARCH 2009 D I N E Z I O E T A L . 729
Despite the relatively low number of DOFs, the
correlation and regression coefficients can be estimated
with 67% confidence for those lags at which the co-
herence is greatest [Fig. 9, solid (dashed) lines indicate
coefficients that are (are not) statistically significant]. Note
that the correlation and regression coefficients corre-
sponding to the theoretical lags (i.e., a 1.0 lag multiplier)
fail the null hypothesis test.
A broadening of the peak correlation arises from
autocorrelation added to the WSC transport time series
by the filtering process, with the 2–12 YBP signal show-
ing a narrower correlation peak and stronger statistical
confidence. Focusing on the 3–12 YBP filtering (the
heavier plot line in Figs. 9a and 9b), we find peaks in the
covariability between the filtered WSC signal and
the FC signal at lag multipliers between 0.1 and 0.5 of the
theoretical adjustment time. Note that the 67% confi-
dence interval shifts from [0.0, 0.6] for the 3–12 YBP
time series to [0.3, 0.5] for the 2–12 YBP time series.
When the same analysis is performed on the bias (y
FIG. 6. (a) Filtered time series of FC transport interannual anomalies. The 20-month gap in
the cable observations is highlighted in gray to indicate the portion of the time series that has
been interpolated for filtering purposes only. (a)–(d) Solid (dashed) line represents the 3–12-yr
(2–12-yr YBP) bandpass-filtered signal. (b) Time series of WSC-driven Sverdrup transport
anomaly over the latitude band centered at 278N in the North Atlantic. The signal is composed
from the three forcing regions using adjustment times 40% of those predicted by standard
theory. The vertical axis in this and all remaining plots of this figure is inverted to facilitate
visual comparison with FC transport in (a). (c) A composite forcing signal like that shown in (b)
but using fully 100% of the adjustment times predicted by linear theory. (d) Time series of
NAO index. The NAO signal is advanced 6 months in time so that the anticorrelation with the
FC signal is maximal (r50.76). Sections of all time series that were subject to edge effects from
signal filtering are not shown.
730 JOURNAL OF PHYSICAL OCEANOGRAPHY VOLUME 39
intercept) for each linear regression, no statistically
significant values are obtained for the entire multiplier
range (not shown). Although the confidence interval for
adjustment times in the 3–12 YBP case includes zero,
the fact that the peak correlations for both cases occurs
between 0.0X and 1.0X strongly suggests that first-mode
baroclinic Rossby waves propagate across the basin with
group speeds faster than that dictated by the standard
theory.
As described in the discussion section, this conclusion
is consistent with a variety of recent observational,
modeling, and theoretical studies supporting the exis-
tence of faster baroclinic Rossby waves in the oceans.
Ultimately, the high coherence between the signals,
together with their close scaling to Sverdrup balance,
provides substantial evidence for baroclinic adjustment
to wind variability as a physical mechanism explaining a
significant portion of interannual FC transport varia-
bility.
d. Time-dependent cross-spectral analysis
The regression methodology and results outlined
above imply a dynamical link between low-frequency
WSC variability and FC transport anomalies at similar
frequencies. To explore the robustness of this link over
the duration of the record, we use the technique of
cross-wavelet transform (XWT; Grinsted et al. 2004) to
estimate the time-dependent magnitude and phase of
WSC–FC covariability at the range of frequencies re-
solved by the available record. Unlike traditional cross-
spectral analysis, XWTs can capture variations in co-
herence with time. An XWT is shown in Fig. 10 between
the monthly FC anomaly (with gaps in the record filled
as described in section 2a) and the composite monthly
WSC anomaly corresponding to adjustment times 0.4X
of those of classical theory. This XWT shows both the
phase and the shared spectral power between changes in
WSC forcing (leading signal) and the FC transport (fol-
lowing signal). Darker regions of the graph indicate times
(abscissa) and signal periods (ordinate) at which the FC
and WSC show the highest common power. A ‘‘cone of
influence’’ corresponds to the regions outside the dashed
line; this region indicates those times and frequencies
that may be subject to aliasing as a result of edge effects.
The XWT analysis clearly shows a strong 3-yr and
longer-period coherence between the transport and
WSC forcing time series, which seems to make its first
appearance during the 1990s. Arrows in this diagram
indicate the phase angle at which the signals have the
greatest shared power; thus, the arrows pointing from
FIG. 7. (a) Map of peak negative regression coefficients, at which the lagged WSC field projects onto the
3–12-yr (3–12 YBP) bandpass-filtered FC transport with greatest negative slope. The linear regressions
are computed for each ;28328grid cell of the NCEP–NCAR reanalysis, throughout the three forcing
regions centered on the 278N band, for the period between 1982 and 2007. (b) Map of lag times in months
at which the WSC field projects onto the 3–12 YBP filtered FC transport with greatest negative slope.
These lags correspond to the peak regression coefficients shown in (a).
MARCH 2009 D I N E Z I O E T A L . 731
right to left in the central dark-gray zone indicate anti-
correlation. The heavy line indicates areas where the
cross-spectral power shown is distinct from the null hy-
pothesis with 67% or greater confidence. In this type of
analysis, the null hypothesis is that both processes are
red noise, in this case univariate lag-1 autoregressive
processes (AR1).
Anticorrelated variability is also observed at periods
of two years during much of the record. This covari-
ability has maximum power in 1994–98, when the co-
herence between the forcing and transport signals was
relatively weak (cf. Figs. 6a and 6b). This coincides with
a part of the FC transport record when 2-yr variability
appears to have had its greatest relative power but
where the WSC signal does not show a particularly strong
biennial periodicity. Note that some of the highest in-
terannual variability overlaps the period 1998–2000,
during which a 20-month-long gap in the cable record
had to be filled. This is a potential weakness of the
analysis. However, as shown in Fig. 9, the correlation
between the 3–12 YBP time series remains significant
when the data from the filled gap is excluded from the
analysis. At periods longer than eight years, the trans-
port record is simply too short to analyze. Analysis of
longer time series records would be necessary to con-
firm the apparent time dependence of coherences at
these interannual frequencies.
4. Discussion
a. Baroclinic adjustment–Rossby wave theory and
recent observations
Using data from the Ocean Topography Experiment
(TOPEX)/Poseidon (T/P) satellite mission, CS96 showed
that in extratropical regions (outside 108S2108N),
westward-propagating patterns in sea surface height
anomalies (SHAs)—which they characterized as the
signature of first-mode baroclinic Rossby waves—
propagate faster than predicted by the standard theory
assuming a beta plane, no mean background flow, and a
flat bottom. The discrepancy between the observed
phase speeds and the theoretical values increases with
latitude from a factor of 1.5 times faster in the tropics up
to 4 times faster in the subpolar oceans. Most of their
estimates in the subtropics correspond to the Pacific
Ocean, where the amplification factor is approximately
2 at about 308N. This value is within the estimated
confidence intervals of the lag multipliers of peak co-
herence shown in Fig. 9.
Subsequent theories motivated by CS96 support the
idea that linear theory may be a lower bound for plan-
etary wave propagation speeds. These theories attribute
increased phase speeds to a diverse number of factors,
such as the effect of the baroclinic mean circulation on
potential vorticity gradients (Killworth et al. 1997;
Killworth and Blundell 2005), interaction of baroclinic
mode waves with topography (Tailleux and McWilliams
2000, 2001), the effect of baroclinic instability (Isachsen
et al. 2007), coupling with the atmosphere (White et al,
1998), and the inclusion of full latitude dependence for
the Coriolis frequency in the equations of motion on a
sphere (Paldor et al. 2007). Dispersion relationships
computed numerically by Paldor et al. (2007), based on
the shallow-water equations on a sphere, predict plan-
etary waves with a phase speed amplification factor that
increases with latitude, consistent with the results of
CS96. Killworth and Blundell (2005) used hydrographic
observations to estimate the effect of baroclinicity on
the potential vorticity gradient. They estimate zonally av-
eraged group speeds for long-limit westward-propagating
Rossby waves between 5 and 10 cm s
21
at about 308N,
which are consistent with the lag multipliers shown in
Fig. 9. Note that our estimates of adjustment speeds
(group speeds) can be compared with the phase speeds
estimated by previous studies because we are discussing
Rossby waves in the long wave limit.
FIG. 8. Correlation coefficient between the 3–12-yr bandpass-
filtered (3–12 YBP) FC transport time series and the 3–12 YBP
filtered WSC time series corresponding to each forcing region,
using a range of lag times in months. Correlation coefficients that
are statistically significant at the 67% confidence level are con-
nected by solid lines; dashed lines connect correlations that lack
statistical significance. In addition, lags at which the low-frequency
WSC–FC correlation is statistically indistinguishable from that of
the peak with 67% confidence are bounded by square brackets,
providing an estimate of the statistical significance of the peak lags.
732 JOURNAL OF PHYSICAL OCEANOGRAPHY VOLUME 39
Zang and Wunsch (1999, hereafter ZW99) performed
a methodologically improved analysis using a longer
T/P dataset (5 yr as opposed to 2 yr by CS96) and found
westward-propagating SHA patterns with phase speeds
that are indistinguishable from those predicted by the
simplest theory for free linear flat-bottom first-mode
baroclinic Rossby waves in the long wave limit. Polito
and Liu (2003, hereafter PL03) report a conclusion
similar to ZW99 based on analysis of a longer (1993–
2000), global T/P dataset using a different methodology.
Their zonal averages of phase speed propagation esti-
mated for each basin separately, for planetary waves
with periods up to 24 months, suggest no more than a
25% high bias in T/P-derived phase speeds compared
with linear theory.
The observational analyses of ZW99 and PL03 sug-
gest phase-speed amplification factors closer to 1, quite
distinct from the factor of approximately 2 to 3, implied
by the signal coherences found in our study (section 3c).
However, the results of ZW99 are representative of
only one latitude band in the Pacific Ocean (their areas
3 and 4, between 188and 228N), while the PL03 results
are zonal averages. Moreover, there is observational
and theoretical evidence for zonal variations in adjust-
ment times. The analysis of T/P data by Schlax and
Chelton (1994) shows an increase in wave amplitude
and westward speed caused by interaction with major
topographic features, for example, in the North Atlantic,
the phase speed of baroclinic Rossby waves appears to
change abruptly over the Mid-Atlantic Ridge. Fur-
thermore, Tailleux and McWilliams (2000) demonstrate
that in a 2–layer beta–plane model, steep topography
enhances the phase of Rossby waves by a factor of H/H
2
,
where His total ocean depth, and H
2
is the depth of the
deeper layer. According to these studies, the effect of to-
pography may explain the enhancement of phase speed
west from the mid-Atlantic observed in the T/P data and
could also explain, at least qualitatively, the spatial dis-
tribution of adjustment times identified in our study (Fig.
7b). Considering the unsettled nature of these questions,
the signal coherences found in our study should not be
ruled out as evidence of real adjustment processes.
b. Other mechanisms influencing FC interannual
variability
Other wind forcing mechanisms influencing the FC
variability on shorter time scales, such as those found to
drive the seasonal cycle, were considered because they
can remain operative on longer time scales. For in-
stance, observations of local wind stress forcing, and
topographic wind stress forcing over the western con-
tinental slope of the North Atlantic were analyzed
consistent with the model studies of Anderson and
Corry (1985a,b), Fanning et al. (1994), and Greatbatch
et al. (1995). Following the same methodology used to
test the baroclinic adjustment hypothesis, coherence is
FIG. 9. (a) Correlation and (b) regression coefficients between the FC transport time series
and the integrated WSC-driven Sverdrup signals (refer to section 3b). In both diagrams, each
point on the abscissa is a multiplier of the standard adjustment times in Table 1. The ordinate
shows (a) or (b) between the FC transport and the WSC-driven Sverdrup signal at that lag
multiplier. Both diagrams show lag regression curves calculated using bandpass-filtered time
series with low-pass filter cutoffs of 24 (2–12) and 36 months (3–12 YBP). Correlation and
regression coefficients that are distinct from the null hypothesis with 67% probability are
plotted as solid lines; dashed lines represent coefficients that lack statistical significance. In
addition, the ranges of lag multipliers at which the regression coefficients are undistinguishable
from the peak with 67% probability are bounded by square brackets, which show the statistical
confidence of the lag multiplier. The significance or lack thereof for the coefficients themselves
is represented by the use of solid and dashed line segments, respectively.
MARCH 2009 D I N E Z I O E T A L . 733
identified between the cable-derived FC transport and
both local and remote wind stress forcing along regions
of the western continental slope of the North Atlantic
Ocean. However, the coherence is of relatively less
importance than that found for the WSC forcing (r,
0.5). Furthermore, the adjustment times implied are on
the order of one year, a result that is more difficult to
reconcile with the fast adjustment times expected from
the coastal trapped waves involved in this type of re-
sponse. For this reason, we do not consider coastal wind
stress forcing in detail in this paper.
5. Summary and conclusions
The main finding of this paper is that interannual
variability of reanalysis-derived wind stress curl (WSC)
over the latitude band of the Straits of Florida explains
about half of the interannual variance (r
2
50.5) of the
cable-derived FC transport with 67% statistical signifi-
cance. Our linear regression results summarized in Fig.
9 indicate both correlation and regression coefficients
of about 0.7 and a regression bias statistically indistin-
guishable from zero, using a presumed lag equal to
40% of the theoretical first-mode baroclinic adjustment
times. These observed lag times imply adjustment by
long-limit baroclinic Rossby waves propagating at
group speeds considerably faster than those predicted
by classical linear theory assuming a beta plane and
flat bottom. This observational estimate is qualitatively
consistent with the majority of theoretical and obser-
vational studies that have followed the analysis of sat-
ellite sea surface height observations by CS96. The
faster Rossby waves implied by the lags estimated in our
study may be reconciled with the literature if zonal
variation in the propagation speeds are considered. The
strong contrast in the spatial distribution of observed
lags between the western and the eastern basins in the
subtropical North Atlantic is suggestive of waves being
sped up because of interactions with the Mid-Atlantic
Ridge. Killworth and Blundell (2005), Tailleux and
McWilliams (2000, 2001), and Paldor et al. (2007) all
provide complementary theoretical frameworks that
help explain the adjustment times estimated by our re-
gression analysis. However, a consensus Rossby wave
theory, not yet available, would be of great value in
interpreting results like ours. Nevertheless, based on the
significance of the signal coherence, signal scaling rela-
tive to Sverdrup balance, and the spatial distribution of
the implied lags identified in this study, we conclude
that the observed interannual variability of the FC
transport can be attributed in large part to baroclinic
adjustment of the North Atlantic subtropical gyre to
low-frequency changes in wind forcing. Ultimately,
longer records of transport estimates are needed to
improve the statistical confidence of our results, and a
richer theoretical framework is needed to understand
the observed physics with more detail.
The amplitude of variability at interannual frequen-
cies shows notable time dependence, in both the spec-
trum of FC transport and the cross-spectrum between
FC transport and WSC forcing over the 278N latitude
band. Insufficient data exist from the cable measure-
ment of FC transport considered in this study to analyze
either the statistical properties of this time dependence
or to determine its possible physical mechanisms from
these data. However, this does point to an area of po-
tentially fertile study, using both earlier records of di-
rect observations and proxies such as coastal sea level
data, which may reliably extend the available record
length of the FC transport time series to allow decadal
and longer-period signals to be analyzed within it.
Analysis of the global satellite altimetry dataset, now
twice as long as in any of the studies cited above, should
shed considerable new light on the zonal variation of
propagation speeds of long-limit Rossby waves in the
real North Atlantic. Improved estimation of the baro-
clinic adjustment times in the western subtropical North
Atlantic is crucial for the inference relating FC transport
variability to WSC on interannual scales. Current efforts
FIG. 10. XWT between the monthly time series of FC cable data
and the monthly WSC forcing signal combined using adjustment
times 40% of those predicted by linear theory (Table 1). The re-
gion outside the dashed line corresponds to those times and fre-
quencies that may be subject to aliasing as a result of edge effects.
The solid line delimits those times and frequencies when the
shared power is significant with respect to null hypothesis (i.e.,
both signals are AR1 processes) with 67% confidence. The gray-
scale shows cross-wavelet power on an arbitrary scale in which
darker colors indicate higher power. Arrows indicate the phase
angle of greatest coherence; thus, arrows pointing from right to left
indicate anticorrelation.
734 JOURNAL OF PHYSICAL OCEANOGRAPHY VOLUME 39
to predict interannual changes in North Atlantic circu-
lation (Meinen et al. 2007) could benefit from refined
understanding of FC–WSC low-frequency variability,
such as is outlined in this paper.
As previously mentioned, we find that wind forcing
explains 50% of the interannual variability of the Florida
Current. Low-frequency wind stress variations associated
with coastal wave phenomena may also play some role in
forcing interannual FC variability, but our analysis indi-
cates this is likely to be of secondary importance. In ad-
dition, it is unclear how these coastal forcing mechanisms
could link NAO and FC low-frequency variability. How-
ever, part of the unexplained FC variance could result
from MOC variability, since the FC is a return pathway
both for the wind-driven gyre circulation and the At-
lantic MOC (Schmitz and Richardson 1991). Charac-
terizing the covariance between interannual variability
in wind forcing and FC transport, as we have done in
this study, could facilitate the analysis of MOC signals in
the total transport time series. Monitoring this compo-
nent of the Atlantic MOC is of great importance, since it
is closely related to the interhemispheric water ex-
change that supports the northward heat transport of
the Atlantic Ocean, a major feature of the global climate.
To conclude, the spatial pattern of NAO-correlated
WSC interannual variability indicates that high (low)
NAO produces positive (negative) WSC anomalies in
the western and central North Atlantic between 208and
308N, that when scaled according to the Sverdrup bal-
ance are sufficient to drive much of the observed in-
terannual variability in the FC transport. This feature of
the low-frequency NAO–WSC pattern has not been
previously highlighted, owing perhaps to the much
larger anticyclonic WSC signal located further north
and to the idea that this may be the dominant driver of
the observed FC–NAO correlation (e.g., Baringer and
Larsen 2001) appears to be new. Our suggestion, there-
fore, that baroclinic adjustment is operative, at the time
scales investigated in this study, provides a physically
plausible mechanism to explain the FC–NAO anticorre-
lation identified by previous studies. Further analysis
with longer FC transport records could both confirm
the physicality of this mechanism with more certainty
and allow exploration of its role in explaining FC variability
at decadal and longer time scales.
Acknowledgments. NCEP–NCAR reanalysis data
are provided by the NOAA/OAR/ESRL PSD (available
online at http://www.cdc.noaa.gov/cdc/data.ncep.reanalysis.
derived.surfaceflux.html). The Florida Current cable
and section data on NOAA’s Atlantic Oceanographic
and Meteorological Laboratory (AOML) Web site
(available online at http://www.aoml.noaa.gov/phod/
floridacurrent) and are funded by the NOAA Office of
Climate Observations. The NAO index is provided by
NOAA/CPC at their Web site (available on online at
http://www.cpc.noaa.gov/data/teledoc/nao.shtml).
This research was carried out in part under the aus-
pices of CIMAS, a join institute of the University of Mi-
ami and NOAA (Cooperative Agreement NA17RJ1226).
PD and LW were supported by NOAA/AOML and
CIMAS, WJ was supported by NSF Grant OCE-0241438,
and CM and MB were supported by the NOAA Western
Boundary Time Series project.
We thank Remi Tailleux and Peter Killworth for in-
teresting exchanges on recent Rossby wave theories.
Robert Molinari, Sang-Ki Lee, Tony Sturges, and an
anonymous reviewer provided helpful comments that
improved an earlier version of the manuscript. Amy
Clement provided a number of suggestions that helped
improve the statistical analysis of the results. The initial
research for this paper was conducted as part of a
graduate course at the University of Miami, during
which time a classmate, Corinne Hartin, provided both
insight and encouragement. Cross-wavelet and wavelet
coherence software was provided by A. Grinsted. All of
the figures in this paper using maps or time series were
created using the free GMT software package.
REFERENCES
Anderson, D. L. T., and A. E. Gill, 1975: Spin-up of a stratified ocean
with applications to upwelling. Deep-Sea Res., 22, 583–596.
——, and R. A. Corry, 1985a: Seasonal transport variations in the
Florida Straits: A model study. J. Phys. Oceanogr., 15, 773–786.
——, and ——, 1985b: Ocean response to low frequency wind
forcing with application to the seasonal variation in the Flor-
ida Straits–Gulf Stream transport. Prog. Oceanogr., 14, 7–40.
——, K. Bryan, A. E. Gill, and R. C. Pacanowski, 1979: The
transient response of the North Atlantic: Some model studies.
J. Geophys. Res., 84, 4795–4815.
Baringer, M. O., and J. C. Larsen, 2001: Sixteen years of Florida
Current transport at 278N. Geophys. Res. Lett., 28, 3179–3182.
Barnier, B., 1988: A numerical study on the influence of the mid-
Atlantic Ridge on nonlinear first-mode baroclinic Rossby waves
generated by seasonal winds. J. Phys. Oceanogr., 18, 417–433.
Barnston, A. G., and R. E. Livezey, 1987: Classification, season-
ality and persistence of low-frequency atmospheric circulation
patterns. Mon. Wea. Rev., 115, 1083–1126.
Bo
¨ning, C. W., R. Do
¨scher, and R. G. Budich, 1991: Seasonal
transport variation in the western subtropical North Atlantic:
Experiments with an eddy-resolving model. J. Phys. Ocean-
ogr., 21, 1271–1289.
Bryan, F. O., C. W. Bo
¨ning, and W. R. Holland, 1995: On the
midlatitude circulation in a high-resolution model of the
North Atlantic. J. Phys. Oceanogr., 25, 289–305.
Chelton, D. B., and M. G. Schlax, 1996: Global observations of
oceanic Rossby waves. Science, 272, 234–238.
Eden, C., and J. Willebrand, 2001: Mechanism of interannual to
decadal variability in the North Atlantic Circulation. J. Cli-
mate, 14, 2266–2280.
MARCH 2009 D I N E Z I O E T A L . 735
Fanning, A. F., R. J. Greatbatch, A. M. Da Silva, and S. Levitus,
1994: Model-calculated seasonal transport variations through
the Florida Straits: A comparison using different wind-stress
climatologies. J. Phys. Oceanogr., 24, 30–45.
Greatbatch, R. J., Y. Lu, B. deYoung, and J. C. Larsen, 1995: The
variation of transport through the Straits of Florida: A baro-
tropic model study. J. Phys. Oceanogr., 25, 2726–2740.
Grinsted, A., J. C. Moore, and S. Jevrejeva, 2004: Application of the
cross wavelet transform and wavelet coherence to geophysical
time series. Nonlinear Processes Geophys., 11, 561–566.
Hamilton, P., J. C. Larsen, K. D. Leaman, T. N. Lee, and E.
Waddell, 2005: Transports through the Straits of Florida. J.
Phys. Oceanogr., 35, 308–322.
Hogg, N. G., and W. E. Johns, 1995: Western boundary currents.
Rev. Geophys., 33, 1311–1334.
Hong, B. G., W. Sturges, and A. J. Clarke, 2000: Sea level on the
U.S. East Coast: Decadal variability caused by open ocean
wind-curl forcing. J. Phys. Oceanogr., 30, 2088–2098.
Hurrell, J. W., and H. van Loon, 1997: Decadal variations in cli-
mate associated with the North Atlantic Oscillation. Climatic
Change, 36, 301–326.
Isachsen, P. E., J. H. LaCasce, and J. Pedlosky, 2007: Rossby wave
instability and apparent phase speeds in large ocean basins. J.
Phys. Oceanogr., 37, 1177–1191.
Kalnay, E. M., and Coauthors, 1996: The NCEP/NCAR 40-Year
Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437–471.
Killworth, P. D., and J. R. Blundell, 2005: The dispersion relation
for planetary waves in the presence of mean flow and topog-
raphy. Part II: Two-dimensional examples and global results.
J. Phys. Oceanogr., 35, 2110–2133.
——, D. B. Chelton, and R. A. de Szoeke, 1997: The speed of
observed and theoretical long extratropical planetary waves.
J. Phys. Oceanogr., 27, 1946–1966.
Larsen, J. C., 1992: Transport and heat flux of the Florida Current
at 278N derived from cross-stream voltages and profiling data:
Theory and observations. Philos. Trans. Roy. Soc. London,
A338, 169–236.
——, and T. B. Sanford, 1985: Florida Current volume transports
from voltage measurements. Science, 227, 302–304.
Lee, T. N., and E. Williams, 1988: Wind-forced transport fluctua-
tions of the Florida Current. J. Phys. Oceanogr., 18, 937–946.
——, F. A. Schott, and R. Zantopp, 1985: Florida Current: Low-
frequency variability as observed with moored current meters
during April 1982 to June 1983. Science, 227, 298–302.
Leetmaa, A., P. Niiler, and H. Stommel, 1977: Does the Sverdrup
relation account for the mid-Atlantic circulation? J. Mar. Res.,
35, 1–10.
Marshall, J., H. Johnson, and J. Goodman, 2001: A study of the
interaction of the North Atlantic Oscillation with ocean cir-
culation. J. Climate, 14, 1399–1421.
Mayer, D. A., and J. C. Larsen, 1986: Tidal transport in the Florida
Current and its relationship to tidal heights and cable volt-
ages. J. Phys. Oceanogr., 16, 2199–2202.
Meinen, C., S. Garzoli, T. Delworth, and J. Marshall, cited 2007:
Atlantic decadal variability: Combining observations and models
to investigate predictability. [Available online at http://www.
usclivar.org/science_status/AMOC/AOML_DecadalWorkshop
Report_Final.pdf.]
Molinari, R. L., W. D. Wilson, and K. Leaman, 1985: Volume and
heat transports of the Florida Current: April 1982 through
August 1983. Science, 227, 295–297.
Paldor, N., S. Rubin, and A. J. Mariano, 2007: A consistent theory
for linear waves of the shallow-water equations on a rotating
plane in midlatitudes. J. Phys. Oceanogr., 37, 115–128.
Pedlosky, J., 2000: The transmission and transformation of baro-
clinic Rossby waves by topography. J. Phys. Oceanogr., 30,
3077–3101.
——, and M. Spall, 1999: Rossby normal modes in basins with
barriers. J. Phys. Oceanogr., 29, 2332–2349.
Polito, P. S., and W. T. Liu, 2003: Global characterization of
Rossby waves at several spectral bands. J. Geophys. Res., 108,
3018, doi:10.1029/2000JC000607.
Qiu, B., W. Miao, and P. Mu
¨ller, 1997: Propagation and decay of
forced and free baroclinic Rossby waves in off-equatorial
oceans. J. Phys. Oceanogr., 27, 2405–2417.
Richardson, W. S., and W. J. Schmitz Jr., 1965: A technique for the
direct measurement of transport with application to the straits
of Florida. J. Mar. Res., 23, 172–185.
Sanford, T. B., 1982: Temperature transport and motional in-
duction in the Florida Current. J. Mar. Res., 40 (Suppl.),
621–639.
Schlax, M. G., and D. B. Chelton, 1994: Detecting aliased tidal
errors in altimeter height measurements. J. Geophys. Res., 99,
12 603–12 612.
Schmitz, W. Jr., and P. Richardson, 1991: On the sources of the
Florida Current. Deep-Sea Res., 38 (Suppl.), 379–409.
Schott, F. A., and R. Zantopp, 1985: Florida Current: Seasonal and
interannual variability. Science, 227, 308–311.
Stommel, H., 1948: The theory of the electric field induced in deep
ocean currents. J. Mar. Res., 7, 386–392.
Sturges, W., and B. G. Hong, 1995: Wind forcing of the Atlantic
thermocline along 328N at low frequencies. J. Phys. Ocean-
ogr., 25, 1706–1715.
——, ——, and A. J. Clarke, 1998: Decadal wind forcing of the North
Atlantic subtropical gyre. J. Phys. Oceanogr., 28, 659–668.
Sverdrup, H. U., 1947: Wind-driven currents in a baroclinic ocean,
with application to the equatorial currents of the eastern
Pacific. Proc. Natl. Acad. Sci. USA, 33, 318–326.
Tailleux, R., and J. C. McWilliams, 2000: Acceleration, creation,
and depletion of wind-driven, baroclinic Rossby waves over
an ocean ridge. J. Phys. Oceanogr., 30, 2186–2213.
——, and ——, 2001: The effect of bottom pressure decoupling on
the speed of extratropical, baroclinic Rossby waves. J. Phys.
Oceanogr., 31, 1461–1476.
Visbeck, M., E. Chassignet, R. Curry, T. Delworth, B. Dickson,
and G. Krahmann, 2003: The ocean’s response to North
Atlantic Oscillation variability. The North Atlantic Oscilla-
tion, Geophys. Monogr., Vol. 34, Amer. Geophys. Union,
113–146.
White, W. B., 1977: Annual forcing of baroclinic long waves in the
tropical North Pacific. J. Phys. Oceanogr., 7, 50–61.
——, Y. Chao, and C. K. Tai, 1998: Coupling of biennial oceanic
Rossby waves with the overlying atmosphere in the Pacific
basin. J. Phys. Oceanogr., 28, 1236–1251.
Willebrand, J., 1978: Temporal and spatial scales of the wind field
over the North Pacific and North Atlantic. J. Phys. Oceanogr.,
8, 1080–1094.
Wunsch, C., and D. Roemmich, 1985: Is the North Atlantic in
Sverdrup balance? J. Phys. Oceanogr., 15, 1876–1880.
Zang, X. Y., and C. Wunsch, 1999: The observed dispersion rela-
tionship for North Pacific Rossby wave motions. J. Phys.
Oceanogr., 29, 2183–2190.
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