The Deep Western Boundary Current (DWBC) at 34.5
In the South Atlantic at 34.5
Variations of the MOC and the DWBC have historically been studied mostly in
the North Atlantic (e.g., Meinen et al., 2013a; Perez et al., 2015; Srokosz and
Bryden, 2015; Frajka-Williams et al., 2016; and citations therein). This has
mostly been a matter of convenience and proximity, not a reflection on
scientific importance, as theoretical work and numerical models have
suggested that variations in the South Atlantic may be critical to the
stability and flow of the overall MOC system (e.g., Dijkstra, 2007; Drijfhout
et al., 2011; Garzoli and Matano, 2011; Garzoli et al., 2013; Buckley and
Marshall, 2016). Only in the past few years have observations been collected
to study the MOC and/or the DWBC in the South Atlantic region, beginning with
repeated upper ocean expendable bathythermograph (XBT) transects (e.g.,
Garzoli and Baringer, 2007; Dong et al., 2009, 2014) and full-depth hydrographic
sections (e.g., Lumpkin and Speer 2003, 2007; Bryden et al., 2011), and later
adding continuous moored observations at a few locations including
11
True continuous time series observations of the time varying deep limb of the
MOC, the DWBC, are very limited in the South Atlantic. In terms of continuous
measurements of absolute The term “absolute” here refers to
transports which include both a `baroclinic', vertically sheared, component
and a `barotropic', non-sheared, component. Thus “absolute transport” would
include all flow that is operating in a geostrophic manner.
The Southwest Atlantic MOC (SAM) array was first deployed at
34.5
Map illustrating the location of the moored instruments used in this
study. Instrument types are noted in the legend; site names for the original
PIES (yellow squares) are “A” through “D” from west to east; the newer
CPIES (cyan diamonds) site names are “AA” and “BB”, also from west to
east. Filled contours indicate bottom topography from the Smith and Sandwell (1997)
data set. Color contours indicate the time-mean sea-surface
temperature (
Nominal locations, depths, and initial deployment dates of the PIES and CPIES moorings discussed in this paper. Note: the first instrument at Site B was a CPIES, but it was replaced with a PIES in July 2011.
The array location was selected to be just north of the northern edge of the
meander window of the Brazil–Malvinas Confluence (e.g., Gordon and Greengrove,
1986; Olson et al., 1988; Garzoli 1993; Goni et al., 1996, 2011; Lumpkin and
Garzoli, 2011) based on altimeter, sea-surface temperature (SST), and surface
drifting buoy measurements. Depending on the precise indicator of the
Brazil–Malvinas Confluence selected, the seasonal movement of the
Brazil–Malvinas Confluence is characterized either by meridional shifts
centered near 38.5
Based on recommendations from the broad South Atlantic Meridional
Overturning Circulation (SAMOC) Initiative (see
The analysis of PIES data has become more commonplace within the scientific community over the past few decades, and their use to study the DWBC and the MOC in both the North and South Atlantic has been well documented (e.g., Meinen et al., 2006, 2012, 2013a, b). Therefore, the PIES analysis methods will only be summarized here briefly, with the remainder of the methodology details left to the references cited.
A PIES makes two measurements every hour: (1) the bottom pressure and (2) the
vertical round-trip travel time required for a 12 kHz acoustic pulse to
travel from the bottom moored instrument up to the sea surface and back. The
bottom pressure measurement is made with a highly precise Paros pressure
gauge (e.g., Watts and Kontoyiannis 1990; Donohue et al., 2010), while the
round-trip travel time is determined using a transducer and a high-quality
crystal clock (e.g., Rossby, 1969; Watts and Rossby, 1977; Tracey and Watts,
1986). The travel-time measurements from each PIES are calibrated into
daily, full-water-column profiles of temperature, salinity, and specific
volume anomaly via hydrography-derived look-up tables using the Gravest
Empirical Mode (GEM) technique (e.g., Meinen and Watts, 2000). The application
of the GEM method to the PIES in the SAM array was first done in Meinen et al. (2012) Note: It was recently discovered that, due to a coding
mistake, the time-varying bottom-pressure derived term in the absolute
velocity in the 2012 study was added with the incorrect sign. The full time
series has been recomputed for the present study. Although the character of
the absolute-transport time series changes due to this mistake, the major
results of the earlier study were not impacted.
The combined observations made by an array of PIESs are powerful, as when
combined with the GEM look-up tables they can provide an estimate of the
absolute geostrophic velocity, i.e., the combined baroclinic
(vertically sheared) plus barotropic (depth-independent) flow, as follows.
Vertically integrating the specific volume anomaly profiles generated from
the GEM fields and the PIES travel-time measurements yields daily dynamic
height anomaly profiles at each of the four instrument sites. Differences in
dynamic height anomaly profiles between neighboring PIES sites provide
relative geostrophic velocity profiles orthogonal to the line between the
PIESs (the “baroclinic” component of the velocity; e.g., Meinen et al., 2006).
Differences in bottom pressure from neighboring PIES sites provide absolute
geostrophic velocity variability at the bottom that can be used to reference
the relative velocity profiles (the “barotropic” component of the velocity;
e.g., Meinen and Watts, 2000). Due to the well-known leveling problem, the
time-mean absolute geostrophic velocity at the bottom cannot be determined
from the bottom pressure differences (e.g., Donohue et al., 2010). The
additional measurement of water velocity made by the CPIESs can characterize
the flow 50 m above the seafloor. However, given that the two CPIESs were
deployed much further apart than the typical velocity decorrelation length
scale (e.g., Donohue et al., 2010), and given that there are only measurements
at two locations (Fig. 1), these velocity observations are too sparse to
solve the time-mean absolute-velocity reference issue. As such those
velocity measurements will not be discussed further in this article, and for
the purposes of this study the PIESs and CPIESs will be treated
interchangeably. As time variability is the focus of this paper, the
time-mean issue is not crucial for this study. However, to provide
reasonable time-mean absolute-velocity profiles for discussion, the
time-mean velocity from an ocean general circulation model (the model is
described in the next section) at 1500 dbar was added to the velocity
profiles created using the PIES data Note that in the earlier
Meinen et al. (2012) study the model mean velocity was added near the
bottom; however, for this study the model velocity at 1500 dbar was used to
avoid the significant ageostrophic velocity components in the model in the
nearest-bottom grid cell. The results are not highly sensitive to this
choice of reference level. Also the time-mean meridional velocities are
quite similar if other numerical models are used in place of OFES, e.g., NEMO
(see the description of the NEMO run used in Meinen et al., 2013b). For
example, the time-mean meridional velocity for the vertical grid cell
nearest 1500 dbar, averaged zonally between 51.5 and
44.5
Most of the detailed testing of PIES-GEM estimated velocities and transports
has been done in the North Atlantic where independent estimates were
available at concurrent locations – specifically for the DWBC, this has been
done at 26.5 Note that, like all bottom pressure gauges, the
PIES bottom pressure sensors are subject to exponential and/or linear drift
problems. These drifts have been removed via the standard methods (e.g.,
Donohue et al., 2010) in the analysis presented herein; however, variations
with periods longer than the record length of each PIES deployment
(
The GEM look-up tables used herein are based on a data set of 200 CTD profiles and 365 Argo profiles collected before the end of 2008. See Meinen et al. (2012) for more detail and an example GEM look-up table. Since the beginning of the SAM project, quasi-annual CTD sections have been collected along the PIES line, both to provide concurrent calibration for the PIES travel times and to observe finer-scale and better horizontal resolution water-mass changes over time. These CTD data have not been incorporated into the GEM fields, and as such they represent an independent data set. For this study, CTD sections from July 2010, December 2010, July 2011, and December 2012 are averaged in a fairly simple manner solely to provide an overview of the major water masses. The CTDs collected right at the PIES sites were also used to calibrate the PIES-measured travel times into the corresponding travel times that would be observed on a common pressure level (e.g., Meinen and Watts, 1998).
Time-mean meridional velocity from the PIES data (left panels) and
from the OFES model (right panels). For the data-based mean sections: top
panel indicates the mean over the full 5-year period for which data are
available at the four PIES sites (denoted as yellow boxes on bottom axis);
middle panel indicates the mean over only the
To aid in the interpretation of the observations from the PIES array at
34.5
Average sections of in situ temperature
The time-mean absolute-velocity section calculated from the PIES data during
2009–2014 via the methods described above shows the Brazil Current flowing
southward between PIES sites A and B between the surface and roughly 800 dbar,
with the DWBC flowing southward below it (Fig. 2a). These flows
appear weak and smooth horizontally; however, keep in mind that because
these velocities are calculated via the geostrophic method they represent a
horizontal average between each pair of PIES sites – i.e., horizontal
averages over 2–3
The basic structure of the mean velocity section from the OFES model (Fig. 2b) compares favorably with the mean section from the data (Fig. 2a), albeit with more finely resolved horizontal structure. Additional horizontal information is available from the PIES/CPIES array during the final 2 years – but before looking at that structure it is instructive to first evaluate the time-mean velocities derived from the original four-PIES array only during the final 2-year period (Fig. 2c). The roughly 2-year average is similar to the 4.5 year average (compare Fig. 2a and c), with the upper layer recirculation being slightly stronger and the deep ocean recirculation being slightly weaker or even slightly southward at some depths during the shorter 2-year average. Averaging the model velocity output between pairs of PIESs to simulate the geostrophic averaging (Fig. 2d) yields a section that is qualitatively similar to the 2-year average from the PIES in terms of horizontal and vertical structure, although there are some differences in intensity (compare Fig. 2c and d).
Schematic section illustrating the observed deep water masses and
their time-mean flow direction across the section. Water-mass definitions
are as noted in the text, with the direction of flow denoted with either an
“x” or an “o” as noted. Time mean is determined over the December
2012–October 2014 time period when all six PIES/CPIES sites are available.
Water masses are determined using the PIES
Including the two CPIES records enhances the horizontal structure of the time-mean section, with a more evident Brazil Current core, a stronger upper ocean recirculation core, and a deep recirculation cell that extends to the bottom (Fig. 2e). The model velocity output averaged between the six sites (Fig. 2f) is quite similar to the PIES/CPIES velocity section, although the northward recirculation in the model is weaker than observed both near the surface and at depth. An important point to remember is that the time-mean model velocity at 1500 dbar was used to set the time-mean PIES flow at that pressure level as mentioned earlier (see dashed black lines in Fig. 2), so there is perfect agreement between the PIES/CPIES time-mean velocity and the model velocity at 1500 dbar by construction. (Apparent differences at 1500 dbar are contouring artifacts only.)
As noted earlier, at 34.5 Antarctic Intermediate Water (AAIW): salinity less than 34.25 psu; Upper Circumpolar Deep Water (UCDW): neutral density between 27.75 and
27.90 kg m North Atlantic Deep Water (NADW): neutral density between 27.90 and 28.10 kg m Lower Circumpolar Deep Water (LCDW): neutral density between 28.06 and
28.20 kg m Antarctic Bottom Water (AABW): potential temperature less than
0
Based on these definitions, the layering of the water column along the SAM
array clearly shows AAIW overlaying UCDW, which overlays NADW, which
overlays LCDW, which finally overlays the AABW. These are most evident in
the oxygen section (Fig. 3c), with the enhanced oxygen values of the AAIW
around 900 dbar, the NADW around 2800 dbar, and the AABW around 4800 dbar
standing out from the comparatively lower oxygen waters of the UCDW and
LCDW.
The time-mean locations of the main DWBC water-mass interfaces demonstrate
some rather surprising results when overlain on the time-mean meridional
velocity section (Fig. 4). Very near the continental slope, the NADW is
carried southward as one would expect in the DWBC; however, immediately
offshore the entire NADW layer is being carried northward,
essentially heading back toward the northern formation regions, although the
array provides no information on how far to the north these waters are
carried beyond 34.5
The historical observations of the flow in this region have primarily been
geostrophic estimates relative to an assumed level of no motion, which
absolute-velocity observations here and elsewhere in the DWBC have called
into question (e.g., Meinen et al., 2012, 2013a). The few absolute-velocity
observations that have been obtained previously in the region, Lagrangian
float and direct current meter measurements around 28–30
As has been noted at several other latitudes along the pathway of the DWBC,
the temporal variability of the DWBC flow greatly exceeds the time-mean
values (e.g., Schott et al., 2004, 2005; Toole et al., 2011; Johns et al., 2008;
Send et al., 2011; Hummels et al., 2015). The deep-flow variability at
34.5 Some might suspect this high correlation could be
artificial due to the calculation of transport via the single “gravest” mode
inherent in the PIES/CPIES analysis technique. While a single “mode” is used
in this manner, a similar correlation analysis of the deep transport
integrated in the OFES model yields a very similar high value (
Hovmoller plots illustrating the 30-day low-pass-filtered (LPF) meridional absolute transports integrated in three layers as noted in the panel titles. Transports are cumulatively integrated offshore from the shallowest site eastward toward the center of the basin. Bold white contour indicates zero meridional flow. Symbols along the bottom axes indicate the location of the PIESs and CPIESs; the upper panels show the time periods when all six sites were available.
Integrating the meridional transport through the largest possible DWBC layer,
from 800 down to 4800 dbar and across the entire array between sites A
and D, it becomes clear that these strong events can reverse the deep flow
for periods of a few days to a few months (Fig. 6, black solid line; see
also Table 2 for volume transport statistics) Note that the
transport integrated over the full record (2009–2014) within the 800–4800 dbar
level from sites A to D does not use the data from sites AA and BB,
as those two sites are only available during 2012–2014. Because of the
sloping topography, the transports integrated with or without sites AA and BB
are slightly different, due to the well-known “bottom triangle” issue; however, the differences are very small. For the period when all sites are
available, the transports calculated either with or without sites AA and BB
are correlated with each other with a value of
Statistics for the volume transport calculated from the PIES and GEM data. The transports were integrated from sites A to D (see Table 1) and from 800 down to 4800 dbar (or the bottom, where it is shallower). Statistics were calculated over the period 2009 to 2014 using only the original PIES moorings.
Time series of DWBC volume transport determined across the full horizontal span of the array and integrated vertically from 800 to 4800 dbar (or the bottom for areas where it is shallower). The total absolute transport is shown (black solid), as are the components relative to an assumed level of no motion at 800 dbar (“Relative”; blue dashed) and associated with the actual reference layer flow (“Reference Layer”; red dash–dot). The gray horizontal solid and dashed lines respectively indicate the time mean and the time mean plus or minus two standard errors of the mean (i.e., the 95 % confidence limit for the mean value). Standard errors were determined following commonly used methods (e.g., Dewar and Bane, 1985).
The DWBC variability is demonstrated clearly by the large standard deviation
(22.8 Sv) and the wide peak-to-peak range (139.4 Sv; see also Table 2). Even
after smoothing with a 30-day low-pass filter, the standard deviation is
large (20.8 Sv) and the peak-to-peak range exceeds 95 Sv. These variations
are somewhat larger than the
The mechanisms behind these large variations will be addressed later in the
paper, but before continuing to that topic it is instructive to further
characterize the nature of the variations themselves. The transport can be
broken into a component relative to an assumed reference level of no motion
(e.g., the “baroclinic”, or vertically sheared, component, Fig. 6, blue
dashed line) and a component associated with the actual reference level
velocity (e.g., the “barotropic”, or vertically constant, non-sheared,
component, Fig. 6, red dash–dot line). The former is calculated here
relative to an assumed zero flow at 800 dbar, while the latter is simply the
true reference level (800 dbar) velocity multiplied by the DWBC integration
area. It immediately becomes evident that the transport relative to an
assumed level of no motion at 800 dbar (Fig. 6, blue dashed line) bears
little relationship to the true absolute transport in the DWBC layer (Fig. 6,
black solid line). The relative contribution to the absolute flow is much
smaller than the reference layer contribution, and the two components are
statistically uncorrelated with one another (
Annual cycle of DWBC volume transport (integrated 800–4800 dbar across the entire array); transport anomalies are shown relative to the record-length mean. Gray lines are individual years; red line is the average of all years. Transport time series was low-pass filtered with a 30-day cutoff period to reduce the higher frequency signals.
When the first year of data at 34.5
Spectral analysis of the continuous portion (2011–2014) of the absolute-transport time series (integrated from sites A to D) finds little energy
at either the semi-annual or annual periods, with the largest signature being
a broad peak spanning periods of 90–160 days centered near 145 days (Fig. 8;
spectra are plotted in variance-preserving form, so the area under the
curve is proportional to the energy at each period). The relatively short
record compared to this timescale results in fairly wide error bars for the
spectrum, so the spectral distribution may yield more nuanced results once a
few more years of data have been collected. There are noisy spectral peaks in
the 20–50 day band. Previous observations focusing on the upper ocean just
south of the SAM array (near 37 to 38
Distribution of variance in the indicated period bands in the DWBC transport calculated from the PIES/CPIES observations during the continuous 2011–2014 window. The observed DWBC transport was integrated between 800 and 4800 dbar and between the original PIES at sites A and D. Values for transport integrated only between the PIES at sites A and B are shown in parentheses.
Characterizing the nature of these flow variations could be approached via
Empirical Orthogonal Function analysis (e.g., Emery and Thomson, 1997); however, the resulting eigenvalues are not statistically significant from one
another – i.e., they are “degenerate” (North et al., 1982) and cannot be
physically interpreted in a meaningful way, which may be at least partially
due to the relatively short record length. Instead, to characterize the
vertical-horizontal structure of these transport variations, composite
averages were created based on the transport integrated from 800 to 4800 dbar
(or the bottom where shallower) and from sites A to D (i.e., the
black line in Fig. 6). Composite mean sections of meridional velocity were
created for “strong” days, where the southward transport, integrated within
the above-described bounds, was greater than the record-length time mean
plus two statistical standard errors of the mean (the standard error was
estimated to be 5.2 Sv based on the estimated integral timescale of 17 days;
see solid and dashed gray lines in Fig. 6), for “weak days” where
the southward transport was less than the record-length time mean minus two
statistical standard errors of the mean, and for “middle” days with
transports within
Variance-preserving spectrum of the DWBC volume transport using the continuous record that begins in July 2011. Spectrum determined using Welch's averaged periodogram method and a 2-year window allowing 1 year of overlap. Gray shading indicates the 95 % confidence limits. Vertical black dashed lines indicate the annual and semi-annual periods.
Composite meridional velocity sections based on the average of all
data when the enhanced array is in place, December 2012–October 2014 (top
left), the average of all days when the southward DWBC transport is within
The resulting composites suggest that the anomalous flows have a certain
“barotropicity” inshore of around 49
Time series of absolute transport integrated between sites A and B, and between 800 and 4800 dbar (or the bottom), during the period when all instruments were in place. Also shown is the time-mean value (gray solid line) and lines corresponding to the time mean plus or minus 2 standard errors of the mean (gray dashed), i.e., the 95 % confidence limit for the mean value. Standard errors were determined following commonly used methods (e.g., Dewar and Bane, 1985).
To test whether composites based solely on the DWBC flow (and not the
recirculation) might produce a clearer picture with regards to the deep
inshore and offshore meridional flows, an alternate definition for “strong”
and “weak” was developed based only on the deep transport integrated between
sites A and B (Fig. 10). The standard deviation of the deep transport
variability integrated between sites A and B is less than half that of the
deep transport integrated across the entire array (Table 4), but the
peak-to-peak range still exceeds 50 Sv within the narrower span. The
statistical standard error of the mean is 1.1 Sv, and the integral timescale
is about 6 days, suggesting that higher frequencies play a larger role in the
observed variability in the narrower span between sites A and B. The
“strong” and “weak” days in the record were again defined as days where the meridional
transport experienced southward or northward anomalies greater than two
statistical standard errors, respectively. The resulting composites (Fig. 11)
show similarities to the earlier versions (Fig. 9) inshore of about
49
Same as Fig. 9, except that the transport time series used for identifying strong and weak southward transport days was integrated only between sites A and B (i.e., the record in Fig. 10) instead of between sites A and D. White contours in all panels indicate zero flow.
Time series of DWBC volume transport calculated from output of the OFES numerical model run described within the text. Transport was integrated within 800 to 4800 dbar and between the longitudes of the real-world PIES at sites A and D. Top panel: the complete time series of absolute transport, with the every-3-day full resolution, is shown as the black solid line, while the relative and reference contributions calculated as in Fig. 6 are shown in blue dashed and red dash–dot lines, respectively. Bottom panel: annual cycle of the model DWBC transport anomaly, calculated and shown in the same manner as for the observational record shown in Fig. 7.
This apparent anti-correlation between the deep flow near the slope and the
recirculation offshore is somewhat surprising, since as was noted earlier,
there is only a very weak correlation between the flow between pairs of
PIESs. The correlation values between the deep flows integrated in the sites A
to B span and the deep flows integrated in the sites B to C span is
about
Statistics for the volume transport calculated from the PIES and GEM data across the whole array (columns 2 and 3) versus only within the span between sites A and B (columns 4 and 5). Note that column 2 is identical to column 2 in Table 2. The transports were integrated from between the indicated sites (see Table 1) and from 800 down to 4800 dbar (or the bottom where it is shallower). Statistics are shown for both the period 2009 to 2014 (columns 2 and 4) and during the enhanced array period 2012–2014 (columns 3 and 5). The transports were calculated using only the original PIES moorings; the results in the enhanced period are very similar if the CPIESs are also included, as is to be expected for geostrophic calculations.
Time mean and temporal standard deviation (SD) of the volume transport integrated between 800 and 4800 dbar (or the bottom where shallower) and between the indicated PIES locations. The observation-based estimates (middle columns) were calculated over the 2009–2014 time period; the model-based estimates (right two columns) were calculated over the 27-year run described in the text.
Integrating the meridional velocity from the OFES model within the same longitudinal range (between sites A and D) and over the same pressure range (800 to 4800 dbar or the bottom where it is shallower), using the 27 years of model output, yields a robust DWBC with a time mean similar to the observed value (Fig. 12, see also Table 5). While the time-mean values are similar (recall that the model 1500 dbar mean value is imposed on the data, and therefore the means are not completely independent), the time variability from the model is somewhat smaller than that of the real ocean (standard deviation of 16.5 Sv versus 22.8 Sv, respectively). As in the real ocean, there is little sign of an annual cycle in the model DWBC transport – perhaps a hint of anomalous northward flow in the first half of the year (Fig. 12, lower panel), and anomalous southward flow in the second half, but the variability at other timescales clearly dominates. The percentage of variance explained by the annual or semi-annual periods is less than 10 % each (Table 6), although the annual and semi-annual percentage values are a factor of 2–3 larger than the comparable values for the observed time series (Table 3). Because the model output record is much longer than the real data set, it is possible to evaluate how much energy is in the longer periods; evaluation both in period bands (Table 6) and as a spectrum (Fig. 13) illustrates that the DWBC in the model does not have much energy at periods longer than 2 years. Even using extended windows for calculating the spectra does not extract much energy at the longer timescales (compare Fig. 13b, c, and d). What is clear is that the model variability is weaker than that in the actual observations at essentially all timescales (compare Fig. 13a to b–d). Nevertheless, the model does show a broad peak of energy centered around 140–160 days, just as the observations show, so it is clear that in general the model DWBC has similar, if perhaps too weak, variability when compared to that of the real ocean.
Variance-preserving spectra of the DWBC volume transport time
series (integrated from 800 to 4800 dbar and between PIES sites A and D).
Distribution of variance in the indicated period bands in the DWBC transport calculated from the OFES model output. The model DWBC transport was integrated between 800 and 4800 dbar and between the longitudes of the real locations for the PIESs at sites A and D.
Having verified that the DWBC variability in the model is qualitatively
similar to that in the real ocean (for periods shorter than 2 years), it is
reasonable to then “step back” and evaluate a larger domain within the model
to try and identify the sources and/or mechanisms behind the variations observed
near the continental slope. As a first step toward this goal, a Hovmoller
plot of the OFES meridional velocity at the central depth of the NADW near
2600 m across 34.5
Hovmoller plot illustrating the OFES model meridional velocity along
34.5
The westward-propagating features in the model are consistent with Rossby Wave-like features that have been identified at other latitudes (e.g., Meinen and Garzoli, 2014), with propagation speeds that are slightly faster than linear first-mode baroclinic Rossby Wave theory would predict, which is consistent with historical satellite altimeter observations (e.g., Chelton and Schlax, 1996; Polito and Liu, 2003; Osychny and Cornillon, 2004) as well as some recent theoretical work (e.g., Paldor et al., 2007; De Leon and Paldor, 2009). Note that some studies point out that these features are in fact more likely “coherent vortices” rather than Rossby Waves, since they are closed circulation features that can translate properties, which waves cannot do (e.g., Chelton et al., 2007). More recently, Polito and Sato (2015) have shown that the dynamics may in fact be slightly more nuanced, presenting evidence that these eddies tend to “ride” on Rossby Waves.
The closed nature of these westward-propagating features is clear in the
model when the model output is viewed as monthly averages. Perhaps the most
prominent westward-propagating feature in this model run occurs in the latter
half of 1987, with a strong clear southward velocity anomaly propagating
westward from about 44
The long-term mean from the model (Fig. 15a) clearly shows the southward
DWBC hugging the continental slope at the latitude of the PIES/CPIES array
(yellow line), while in the long-term mean field there is only quite weak
circulation in comparison in the offshore portions of the array. The monthly
averages from the model for the final 5 months of 1987 (Fig. 15b–f); however, illustrate the highly energetic flows that can be found offshore at
any particular time. A strong anticyclonic feature, highlighted by the
magenta disc in Fig. 15, slowly propagates westward from August through
December 1987. The radius of the disc of anticyclonic flow, which was
subjectively determined based on the mapped velocities, is roughly 180–200 km
for most of the months shown (except for December, Fig. 15f, when it
drops to around 120 km). The baroclinic Rossby Radius (NH
Velocities from the OFES model at the core of the NADW near 2600 m
depth:
As has been found at other locations along the DWBC path through the
Atlantic, at 34.5
Coupled with analysis of the time-varying flow along the array and analysis of the broader area in a high-quality, high-resolution, well-validated numerical model, the results suggest that the dominant source of transport variations near the continental slope are westward-propagating coherent vortices that superimpose on top of and modulate the intensity of the DWBC flow to yield large southward or northward anomalies depending on the flow associated with the vortices. This suggests that the observing array might be enhanced or improved through the addition of either or both increased horizontal resolution of observations (to more clearly identify these propagating features) and/or the expansion of the array out toward the Mid-Atlantic Ridge (to more completely capture the offshore recirculations). The results also demonstrate the necessity of directly and independently capturing both the “baroclinic” (vertically sheared) and “barotropic” (vertically constant) flows in order to properly understand the absolute-transport variability of the DWBC at this location.
The moored data used in this study are available at
The authors declare that they have no conflict of interest.
The authors would like to thank the ship captains and crews of the NH