Ocean Dynamics (2005) 55: 213–221
DOI 10.1007/s10236-005-0021-6
J. H. LaCasce
Statistics of low frequency currents over the western Norwegian
shelf and slope I: current meters
Received: 10 November 2004 / Accepted: 13 June 2005 / Published online: 25 August 2005
Ó Springer-Verlag 2005
Abstract We examine records from current meters deployed over western Norwegian shelf and slope during the
period of 1976 to present. Though many of the records are
shorter than six months, when taken together they yield a
coherent picture of the field. The mean flow is dominated
by the Norwegian Atlantic Current (NwAC) near the
shelfbreak, with surface velocities of order 60 cm/sec. The
variance is surface-intensified and increases with water
depth over the shelf, but is more homogeneous on the
slope and just offshore. The variability is strongly seasonal over the shelf but much less so over the slope.
Autocorrelations suggest short temporal (1–3 days) and
spatial (10–20 km) scales, consistent with deformationscale eddies. There is evidence for a long range
(O|100|km) correlation at the shelfbreak, in the core of
the NwAC; otherwise the variability is strongly localized.
Keywords Velocity statistics Æ Norwegian Æ Shelf Æ
Slope
1 Introduction
The dominant feature in the shallow, eastern Nordic
Seas is the Norwegian Atlantic Current (NwAC), the
northward continuation of the North Atlantic Current.
The NwAC brings an average volume flux of roughly
seven million cubic meters of warm Atlantic water into
the Norwegian Sea, with a corresponding heat flux of
roughly 0.25 Peta Watts. This heat transport contributes
to the relatively mild climate in Norway compared with
other locations at similar latitudes.
From the perspective of hydrography, the NwAC
appears as a broad slab of warm water, stretching from
the shelfbreak to 300 km offshore (Fig. 1; Mauritzen
(1996)). In contrast, the current’s velocities are
predominantly confined to two compact cores, one near
the 700 m isobath and the other over the 2000 m isobath
(Orvik and Niiler 2002). The former lies near the shelfbreak and latter coincides with the density front between
the Atlantic Water and the colder interior water of the
Nordic Seas. These cores are strikingly narrow, roughly
20–30 km and are about 500 m deep.
The NwAC is strongly steered by topography as it
moves through the Nordic Seas and one can trace the
path of the currents along isobaths (Poulain et al. 1996;
Orvik and Niiler 2002). This is remarkable, given the
surface-intensification of the velocity cores.1
As the NwAC flows through the Norwegian Sea it
becomes both cooler and fresher. How this transformation occurs and how quickly are unresolved issues. A
water parcel advected in the high-velocity cores would
traverse the distance from the Faroes to Spitzbergen in a
matter of months. But the observed temperature changes
in the current indicate a longer exposure to atmospheric
cooling (Mauritzen 1996). So fluid parcels are probably
exiting the cores, perhaps mixing between them as well
as into the Norwegian and Lofoten basins. Lateral
mixing has also been invoked to explain the observed
freshening of the current before it reaches Spitzbergen
(by mixing with the adjacent Norwegian Coastal Current; Mauritzen 1996).
But what causes the mixing? If the NwAC were
baroclinically unstable, it would generate eddies which
would mix the warm Atlantic water laterally. Eddy
activity is clearly seen on the front between the Norwegian Atlantic Current and the Norwegian Coastal
Current in satellite images of sea surface temperature
(Poulain et al. 1996). But in situ velocity measurements
are relatively few and the best recent estimates are based
on a single current meter array (Skagseth and Orvik
Responsible Editor: Phil Dyke
J. H. LaCasce
Norwegian Meteorological Institute, P.O. Box 43,
Blindern, 0313 Oslo, Norway
E-mail: josephhl@met.no
1
We know however that topography exerts a strong influence on
the time-varying currents here (Isachsen et al. 2003), and this may
in turn affect the path of the mean flow.
214
Mooring locations (T>6 months *)
72
70
68
66
64
62
60
5
0
5
10
15
20
25
Fig. 2 The locations of the moorings for the in situ time series. The
time series longer than six months are indicated by asterisks. In this
and the following figures, the topography derives from the etopo5
data set; the contours indicate depths increasing in multiples of
500 m
Fig. 1 The temperature across the Svinøy section. The solid lines
indicate potential density. From this, the NwAC appears to be a
broad surface flow. Courtesy C. Mauritzen and T. Kristiansson
2002). So there is a need for mapping the current using
more widely distributed measurements; this is the present goal.
Hereafter, we will examine velocity statistics from a
set of current meters over the shelf and slope. The
records are non-uniformly distributed and many are
fairly short, but taken together they yield a reasonably
consistent picture of the flow. This in turn can be used to
infer characteristics of the NwAC and its eddy field.
2 Regional characteristics
The current meter records come from instruments deployed by oil companies in regional survey efforts (and
are now archived at the Norwegian Meteorological
Institute). The mooring locations are non-uniformly
distributed and moreover most records are short, i.e.,
less than a year. An exception are four moorings in the
Svinøy region, deployed by the K.A. Orvik at the University of Bergen (Skagseth and Orvik 2002). These are
multi-year records, with the longest spanning some seven years. Taken together, the archive has over 500 records, at the locations shown in Fig. 2.
The records span a range of depths and also times,
from 1976 to present. The sampling rate also varies, from
once a day to once an hour. But because we are interested
in the sub-tidal frequencies, we smoothed all records with
a low-pass filter (with a half-power point of 12 h).
We then generated statistical moments from the
velocities and these are presented in the following sections. We begin with the first moment (the means) and
then the second (variances). For an indication of frequency of extreme events, we examine the velocity
probability density functions. Lastly, we examine temporal correlations from single records and cross-correlations between records at different locations.
3 Means
The mean currents calculated from instruments in the
upper part of the water column are shown in Fig. 3.
These derive from records longer than 60 d, in the depth
range of 20–250 m (if multiple instruments were present
at the same location, their means were averaged,
weighted by record length, to produce a single velocity).
Only means significant at the 95% level are plotted.
The dominant feature is the inner branch of the
NwAC, described above. The current appears distinctly
as an intense northward flow in the region bordered by
the 500 m and 1000 m isobaths. The maximum velocities
at this depth are of order 60 cm/sec. In contrast, the
means offshore and on the shelf are weaker. While significant, they do not indicate a clear pattern to the flow
in these locations; some vectors are northward while
others nearby are southward. Note too that the outer
branch of the NwAC is not resolved, possibly due to the
lack of moorings in its vicinity.
The mean velocities at depth are shown in Fig. 4.
These derive from instruments in the lower 40% of the
water column; as such, the represented depths vary,
215
500 and 1000 m isobaths and has near-surface velocities
of order 60 cm/sec. It is roughly 500–700 m deep and so
is visible near the bottom near the shelfbreak.
4 Variances
Fig. 3 The mean currents from instruments in the depth range of
20–250 m. The only means plotted are those with records longer
than 60 d and which are significant at the 95% level
The variances were calculated from all records longer
than 50 d; variance ellipses corresponding to instruments with depths from 20 to 250 m are shown in Fig. 5.
Several features are evident. First, the variance is greater
offshore of the shelfbreak. If eddies are being generated
over the slope, they are evidently spreading preferentially offshore.
Second, the variability is anisotropic over the slope,
with most ellipses oriented parallel to the isobaths. This
suggests the bottom constrains the surface variations
(despite the significant stratification here; Fig. 1). Offshore the anisotropy and orientation varies with location. Near Svinøy (near 64N, 4E), the ellipses are nearly
isotropic while over the Vøring Plateau (near 67N, 6E),
they have a distinct zonal orientation. Many ellipses on
the shelf are anisotropic but do not exhibit a consistent
orientation relative to the isobaths (although this may
reflect unresolved topographic features; see below).
Third, there is the regional variability. Offshore of the
shelfbreak, the ellipses are similar in most regions, suggesting the variance is largely homogeneous. The variability is comparable at higher and lower latitudes, in the
west and in the east. However, the variance increases
with water depth across the shelf. This is clear if one bins
the standard deviations as a function of water depth
(Fig. 6). The deviations increase systematically crossing
the shelf, but are nearly constant offshore of the 800 m
isobath. The deviations are typically 5–10 cm/sec over
the shelf, increasing to 15 cm/sec offshore.
Fig. 4 The mean currents from instruments in the lower 40% of the
water column. The means again come from records longer than
60 d and are significant at the 95% level
from roughly 100–200 m over the shelf to over 1000 m
offshore.2 As with the surface velocities, the inner
branch of the NwAC is the prominent feature. The
velocities are about 10 cm/sec over the middle slope but
up to 20 cm/sec near the shelfbreak. Elsewhere, on the
shelf and offshore, the means are weak and inconsistently oriented.
The inner branch of the NwAC therefore dominates
the means. It is confined to the slope region, between the
2
In the shallowest regions, only instruments in the upper half of the
water column were used for the shallow statistics, to avoid overlap
with the deep instruments.
Fig. 5 The variance ellipses from all records longer than 50 d, in
the depth range of 20–250 m. If multiple instruments were present
at the same location, their variances were averaged
216
25
15
10
15
10
5
5
0
winter u
winter v
summer u
summer v
20
20
Standard deviation (cm/sec)
Major axis std. dev. (cm/sec)
Seasonal variations (T>20 d, 20<z<250 m)
Deviations; 20<z<250 m; T>50 days
25
0
0
200
400
600
0
800 1000 1200 1400 1600 1800 2000
Water depth
Fig. 6 The standard deviations along the major axis of variability
plotted as a function of water depth. The results come from
instruments in the depth range 20<z<250 m, for records longer
than 50 d
The deep variances are shown in Fig. 7. The variability here is noticeably weaker than near the surface,
consistent with the eddy activity over the slope and
offshore being surface-intensified. Interestingly though,
the deep variances are approximately the same on the
shelf and offshore. As with the surface variances there is
substantial anisotropy, with the greatest fluctuations
being those parallel to the isobaths.
To generate Figs. 5 and 7, we used records from
different years. This was possible because the year to
year changes are relatively small, ie., the variance is
approximately stationary. We exploit stationarity later
on when generating the velocity probability densities
(Sec. 5).
200
400
600
800 1000 1200 1400 1600 1800 2000
Water depth(m)
Fig. 8 Velocity standard deviations for winter and summer months
from all records longer than 20 d, as a function of water depth. The
records have been grouped into three bins, as described in the text
However, there is a degree of seasonality in the variance. To quantify this, we extracted portions from the
records which covered more than 20 d during the winter
or summer periods and combined them to calculate
standard deviations during those seasons. Because the
variance increases with water depth, we divided the data
into three groups: inshore of 500 m, between 500 and
1000 m and offshore of 1000 m. We focused in addition
on the shallow depth range (20–250 m) and projected
the velocities along and across the local isobaths.3
The results (Fig. 8) suggest the variability on the shelf
is about 60% greater during winter than summer. In
addition the standard deviations are about the same
along and across the isobaths. Over the slope, the winter
standard deviations are greater, but only by about 25%.
Moreover, the slope variance is anisotropic with respect
to the topography (and evidently more so in the wintertime). Offshore, the wintertime variability is likewise
only about 25% greater than in the summer. Note the
offshore variance is anisotropic, but greater across the
isobaths; this stems in part from the zonal variability
over the Vøring Plateau.
Thus the greatest variability occurs near the surface,
offshore of the shelfbreak; it is weaker at depth and over
the shelf. Topographic steering is most pronounced over
the slope while seasonality is accentuated over the shelf.
5 Probability densities
Next, we examine the extreme currents, i.e., velocities
exceeding the mean by several standard deviations. Such
3
Fig. 7 The variance ellipses from instruments in the lower 40% of
the water column, from records longer than 50 d
The projection was made onto the etopo5 topographic data set,
smoothed to remove scales smaller than about 15 km. As such, the
along-isobath direction will differ somewhat from reality, depending on the location.
217
c
Fig. 9 a The along- and cross-isobath velocity PDFs offshore of
the shelfbreak, at shallow depths. Only records longer than 30 d
have been used. b The along- and cross-isobath velocity PDFs
offshore of the shelfbreak, in the deep. c The along- and crossisobath velocity PDFs inshore of the shelfbreak
a 10 0
events are infrequent and thus are not well-captured by
the lower statistical moments, like the variance. A
mooring which experiences mostly weak variability but
also occasionally experiences strong currents might have
the same variance as a mooring which sees a constant
level of intermediate variability. To gauge the frequency
of extreme currents, we employ the PDF.
The probability density function (PDF) gauges the
probability of a given velocity occurring (in this case, at
a chosen location and depth). All the statistical moments
(mean, variance, etc.) are derived from it. The central
limit theorem states that if the data has non-infinite
variance, averages of independent sub-samples will have
a Gaussian (‘‘normal’’) PDF as long as the number of
samples is large enough. But coherent flow features, like
jets and vortices, can cause deviations from Gaussian
distributions. PDFs from the open ocean are known to
be weakly non-Gaussian (Bracco et al. 2000; LaCasce
2005), reflecting more energetic events than expected
from a Gaussian process.
Ideally, one uses long records to calculate PDFs because anomalous events occur infrequently. But as stated, only the Svinøy records exceed a couple of years in
duration. So we invoke stationarity (that the PDFs do
not change from year to year) and combine the records
together. We normalize the records by dividing by their
respective standard deviations, prior to combining them.
For a similar analysis, see LaCasce (2005).
An example of a ‘‘reconstructed’’ velocity PDF, from
the shallow offshore region, is shown in Fig. 9a. The
numbers in the upper right corner of the figure are the
kurtoses, defined:
P 4
u
Ku P i i 2
ð i u2i Þ
10 –2
A Gaussian distribution has a kurtosis of three, and
larger kurtoses reflect extended ‘‘wings,’’ i.e., more
occurrences of extreme events. The numbers at upper
left are the significance levels from the Kolmogorov–
Smirnov (K–S) test, a goodness-of-fit test which can be
used to compare an empirical PDF with a Gaussian
(e.g., Press et al. 1992). Values nearer unity reflect an
increased likelihood of a Gaussian distribution; if the
value exceeds 0.05, one cannot rule out a Gaussian
distribution with 95% confidence. To evaluate the K–S
statistic, we must take into account that the daily
velocities are not independent but rather are correlated
over a period of roughly 3 days (Sec. 6).
For Fig. 9a, we used records longer than 30 d (because the mean and standard deviations from shorter
20<Z<250m, H>500m, T>30 days
0.744, 0.882
Along (3.1)
Across (3.1)
10 –1
10 –3
10 –4
–8
–6
–4
–2
0
2
4
6
8
u/std(u)
Z>500m, H>500m, T>30 days
b 10 0
0.010, 0.051
Along (3.6)
Across (4.1)
10 –1
10 –2
10 –3
10 –4
–8
–6
–4
–2
0
2
4
6
8
u/std(u)
c 10 0
H<500m, T>30 days
0.000, 0.000
Along (3.9)
Across (4.7)
10 –1
10 –2
10 –3
10 –4
–8
–6
–4
–2
0
2
4
6
8
u/std(u)
records have lower significance). By taking all records
together like this, the composite time series has over
20,000 d (55 years), much longer than we could hope to
218
Fig. 10 Velocity
autocorrelations from four
instruments in the region.
Shown are the correlations for
the along- and cross-isobath
velocities, as well as
exponentials with comparable
decay rates
Svinoy slope, 700m
Svinoy slope, 100m
Along
Across
exp(t/3)
0.8
0.6
0.6
0.4
0.4
0.2
0.2
0
0
–0.2
0
2
4
6
8
Along
Across
exp(t/1)
0.8
10
–0.2
0
Halten Bank shelf, 50m
0.6
0.4
0.4
0.2
0.2
0
0
0
2
4
6
obtain with one mooring. The normalized PDF for
velocities projected along and across isobaths are plotted
over a Gaussian distribution with unit variance.4 We see
the PDFs are very nearly Gaussian. There are deviations
in the wings, but these are small.
The PDFs at depth are less Gaussian (Fig. 9b). The
kurtoses are 3.6 and 4.1, and the K–S test suggests the
null hypothesis (that the distributions are Gaussian) can
be rejected with 95% and 90% confidence in the alongand cross-isobath directions. The PDFs differ from a
Gaussian because there are too many extreme events and
the cross-isobath velocity is more episodic than the
along-isobath velocity. The distributions are also weakly
skewed, with more extreme events southward and offshore. The individual records which show the largest
kurtoses are those in water deeper than 1000 m, i.e., off
the slope.
The PDFs from the shelf (Fig. 9c) are even less
Gaussian than the deep records offshore. They have
elevated kurtoses and the K–S test indicates rejection of
Gaussianity at the 99% level. The PDFs in fact appear
closer to an exponential distribution. As with the deep
offshore region, it is the cross-isobath velocity which
exhibits the most pronounced wings.
So the PDFs deviate from a Gaussian distribution in
the deep water offshore of the shelfbreak and over the
4
The PDF is normalized. To evaluate the actual strength of the
currents, one must know the standard deviation, as shown in
Fig. 6.
8
6
8
10
Along
Across
exp(t/1.5)
0.8
0.6
–0.2
4
Halten Bank shelf, 250m
Along
Across
exp(t/1.7)
0.8
2
10
–0.2
0
2
4
6
8
10
shelf, due to an excess of large velocity events. The
deviations from Gaussianity are more pronounced in the
cross-isobath velocity. However, the PDFs in the shallow waters offshore of the shelfbreak are nearly Gaussian.
6 Temporal correlations
Next we deduce coherence time scales by calculating
velocity autocorrelations at different locations. The
autocorrelation, with lag s, is defined:
P P
ui ðtÞui ðt þ sÞ
RðsÞ ¼ i t P
;
ð1Þ
i Ni
where the index i refers to the velocity record and the Ni
indicates the number of velocity products for each record (at that lag). Records with gaps are treated as
multiple time series. The autocorrelation is normalized
by the variance so that the value at zero lag is one.
Results for the along- and cross-isobath velocities at two
representative locations are shown in Fig. 10. Also,
shown are exponential autocorrelations with similar
decay times.
The curves for the 100 m instrument at Svinøy are
representative of the behavior in the core of the NwAC
(upper-left panel). The decay in the along-isobath
direction is slower than in the cross-isobath direction;
the comparison exponential has an e-folding time of 3 d
along the isobaths and about 1 d across. Note the decay
219
at short times is actually closer to a Gaussian than an
exponential (probably, indicating a non-trivial decorrelation time for the acceleration; Sawford 1991), but the
exponential yields a better indication of the integral
time. The autocorrelations at 700 m (upper-right panel)
are more isotropic, with integral times of about 1 d in
both directions. The results downstream along the slope,
at Ormen Lange (63.5N, 6E), are very similar to those at
Svinøy, with the longest correlation occurring near the
surface in the along-isobath direction.
Representative examples of the correlations on the
shelf are shown in the lower panels. The correlations
nearer the surface, at 50 m depth, indicate approximately isotropic decay with time scales on the order of
1.5 d. Similar results are found here with a very shallow
instrument, at 2 m depth. They are also similar at 250 m
depth (lower right panel), with isotropic correlations and
a comparable decay time.
So the autocorrelations suggest time scales between 1
and 3 d, with the longest time scales occurring near the
surface and in the core of the NwAC. The estimates are
nearly identical to those inferred previously from surface
drifter data (Poulain et al. 1996).
7 Spatial correlations
Lastly, we address the question of coherence between
simultaneous records at different locations. Such
coherence might occur, for example, with topographic
waves propagating along the isobaths. We calculate
cross correlations by using concurrent records wherever
they exist.
First, we consider the correlations across the slope.
There is a weak correlation, at zero lag, for the 100 m
Fig. 11 Examples of lagged
correlations between different
moorings. The upper panel
pertains to the 100 m
instruments at Svinøy moorings
S2 and SE1, which lie 13 km
apart in the cross-slope
direction. The lower panel
shows the correlations for the
100 m instruments at moorings
S1 and TH7, 94 km apart along
the shelfbreak. The peaks near
zero lag are significant at the
95% level
velocities at the Svinøy moorings S2 and SE1, which lie
over the mid-slope and are about 13 km apart (upper
panel, Fig. 11). The coefficients are similar in both the
along- and cross-isobath directions and are significant at
the 95% level. However, they are not large (r 0.4),
given the small separation. The correlations for the
500 m velocities are less, nearer r=0.25. Moorings S1
(near the shelfbreak) and S2 are about 10 km apart and
yield a similar correlation (r 0.4) at 100 m and weaker
correlations at depth. There is a lag of a few days in the
along-slope correlation between S2 and SE1 (with SE1
leading) but no such lag exists between S1 and S2, so this
is probably insignificant. Moorings S1 and SE1, roughly
24 km apart, are uncorrelated, as are moorings SE1 and
SE2, which are 25 km apart. So there is coherence across
the slope only at scales less than about 15 km.
Then there are the along-slope correlations. For this,
we compare the Svinøy records with those at Ormen
Lange, roughly 100 km to the north. Moorings S1 and
TH7 both lie near the shelfbreak and are about 94 km
apart. Interestingly, they are weakly correlated in the
along-isobath component at 100 m depth (lower-left
panel, Fig. 11); the correlation, with r 0.4, is as large
as that between S2 and SE1; it is significant at the 95%
level and occurs at zero lag. The cross-isobath component, however, is uncorrelated. A similar result holds for
moorings S2 (100 m) and OLI (200 m), which lie over
the mid-slope. But not all the shallow slope instruments
are so correlated; two others (moorings S2 and TH8) are
also about 94 km apart and are uncorrelated in both
directions. Furthermore, the correlation does not exist
deeper down; none of the Svinøy-Ormen Lange deep
instruments are correlated.
What causes the correlation near the surface? One
candidate is coastal trapped waves. Assuming a typical
S2, SE1; 100 m (δx=13km)
0.5
Along
Across
0.4
0.3
0.2
0.1
0
0.1
–0.2
–60
–40
–20
0
20
40
60
S1, TH7; 100 m (δx=94km)
0.5
0.4
0.3
0.2
0.1
0
0.1
–0.2
–100
–80
–60
–40
–20
0
20
40
60
80
100
220
phase speed of about 100 km/d (e.g. Gill, 1982), such a
wave would traverse the distance from Svinøy to Ormen
Lange in about a day. So, with 24 h-filtered velocities, a
lag of zero is possibly consistent with wave propagation.
But the lack of correlation at depth appears to be at
odds with this explanation. More likely is that there are
coherent fluctuations in the NwAC which affect the
along-isobath component for instruments which lie in its
core.
We found no correlations between moorings on the
slope and on the shelf. And the records on the shelf were
mostly uncorrelated as well. An exception was two
moorings inshore of Ormen Lange (named B9 and B11)
which were roughly 17 km apart and were weakly correlated in the cross-isobath velocity. But other similarly
spaced meters were uncorrelated. For example, there
was a cluster of deep instruments all within a 5 km radius which were mostly uncorrelated. The reason was
probably related to the drastic, small scale topographic
variations here (and not captured in the etopo5 data set).
To conclude, the spatial correlations suggest decay
scales of 10–15 km and perhaps less over the shelf. This
is on the low end of the range of scales (10–40 km) inferred previously from drifter data (Poulain et al. 1996).
There is however evidence of coherent variations in the
along-isobath velocity at the shelfbreak over scales of at
least 100 km at the shallower depths, probably due to
fluctuations in the NwAC.
8 Summary
We have examined the statistical moments of the subtidal currents over the western Norwegian shelf and
slope. The moments are as follows:
– The mean is dominated by the inner branch of the
Norwegian Atlantic Current (NwAC), near the
shelfbreak. The NwAC is strongly surface-intensified,
with velocities of order 60 cm/sec at the surface and
falling to near zero near the bottom and is strikingly
narrow, of order 20–30 km. The structure is consistent with that described by Skagseth and Orvik (2002)
at Svinøy (see their Fig. 3). The means elsewhere are
generally weak. We do not resolve the outer branch of
the NwAC, inferred previously from drifter data
(Poulain et al. 1996; Orvik and Niiler 2002).
– The variances are greatest near the surface. They increase with water depth across the shelf, but are
approximately constant over the slope and just offshore. There is significant topographic steering of the
variability over the slope, but less on the shelf. And
there is significant seasonality over the shelf, with
winter fluctuations roughly 50% greater than those in
summer, but less seasonality on the slope.
– The PDFs of the surface velocities are nearly Gaussian
over the slope and offshore. They are however significantly non-Gaussian at depth and over the shelf as
well. The deviations from Gaussianity stem from an
excess of energetic events and are more important in
terms of the cross-isobath flow.
– The temporal correlations indicate Eulerian timescales
of 1–3 days.
– The spatial correlations indicate Eulerian length scales
on the order 10–15 km. The only exception is a possible long-range correlation in the along-isobath
velocities near the shelfbreak.
9 Discussion
From the present results, it appears that the NwAC is
generating eddies roughly 10 km in scale which spread
preferentially offshore. The internal deformation radius
here is also about 10 km, so it is possible the eddies are
the product of baroclinic instability. The offshore
spreading could account for the hydrographic structure
of the inflow, as suggested in (Sec. 1). If so, then there is
presumably a significant offshore heat flux over the
slope. We checked for this (by calculating correlations
between residual temperature and the cross-slope
velocity) but did not obtain significant results, probably
because the records are too short. Temperature records
do exist for the data at Svinøy (Orvik, pers. comm.), so a
heat flux calculation should be possible there.
The usual framework for interpreting current fluctuations on the shelf and slope is in terms of topographic
waves and/or coastally-trapped waves (Rhines 1970; Gill
and Clarke (1974), Allen (1975). In this, forcing (wind,
or an unstable current) excites waves which propagate
along the isobaths, northward in this case. But apart the
core of the NwAC, there is no evidence for correlations
at distances greater than 20 km. This is not to say that
topographic waves do not exist; but if so, they are
incoherent over long distances, perhaps due to topographic scattering.
However, an alternate dynamical framework may be
applicable. This is the notion of geostrophic turbulence
over a slope (e.g., Vallis and Maltrud 1993; LaCasce and
Brink 2000). This concerns an energetic, baroclinic eddy
field in the presence of a topographic grade. In this, the
character of the flow depends on the stratification and
the severity of the slope. With a weak slope and/or weak
stratification, the eddies are nearly barotropic and their
size is controlled by the slope itself. With a strong slope
and/or strong stratification, the eddies are surfaceintensified and deformation scale while the deep flow is
dominated by small-scale topographic waves and possibly jets (LaCasce and Brink 2000).
The present results bear qualitative similarities. The
weak slope case may apply to the shelf, where the variance depends little on depth. These eddies might be
generated by wind-forcing and moreover may co-exist
with topographic waves. The strong slope case may
pertain offshore of the shelfbreak, with the stratification
due to the Atlantic inflow and the steep slope. As in the
turbulence simulations, we observe intense, eddy-like
221
motion in the surface layer and topographically-aligned
variability at depth. The similarities to the turbulence
simulations may be coincidental but do suggest a route
for future investigation.
It is worth noting that the shelf and slope eddy field,
with its time scales of a few days and length scales of
10 km, present formidable difficulties for numerical
models and for current forecasting. Models require fine
resolution, but even then the chaotic nature of the flow
will likely cause a sensitive dependence on initial conditions. We examine how well a state-of-the-art operational model does in simulating the field in the
accompanying paper.
Acknowledgments The work was supported under a grant from the
Norwegian Deep Water Program (NDP) by Norske Shell and by
the Ormen Lange license by Norsk Hydro. Further support was
provided by the NOCLIM program, funded by the Norwegian
Research Foundation. The data were collected and archived under
NDP, except for the Svinøy data, which were graciously provided
by K.A. Orvik, University of Bergen. C. Mauritzen provided useful
input on the local circulation and commentary from two anonymous reviewers helped improve the manuscript.
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