Abstract

Multiyear in situ Eulerian acoustic Doppler current profiler measurements were obtained at 5-, 10-, and 19-m depths off the Big Bend coast, and in 19 m off the Florida Peninsula to the south. Analysis on subinertial time scales, dominated by weatherband frequencies, led to the following conclusions. At the 19-m Big Bend site (K-Tower), consistent with coastally trapped wave (CTW) theory, the along-isobath flow is not proportional to the local along-isobath wind stress, but rather to the alongshore wind stress to the south along the west Florida shelf (WFS). At the southern 19-m site, consistent with previous work, the along-isobath flow is driven by , but is weakened by an alongshore pressure gradient brake. Via CTW dynamics this brake is due to the abrupt “end” of the WFS at the Florida Keys. By contrast, along-isobath flow at the shallow 5-m site is driven by the local wind in a constant stress turbulent frictional layer. Because of the freshwater flux near the coast, density usually increases seaward. This leads to a strong asymmetry in the cross-isobath frictional bottom boundary layer (BBL) flow when the subinertial along-isobath flow direction changes. In one case the BBL flow is shoreward and gravitationally stable while, in the other, the BBL flow is gravitationally unstable as less dense water is forced under more dense water. Seasonal changes in the seaward horizontal density gradient also shear the seasonal along-isobath flow via thermal wind dynamics.

1. Introduction

The wide west Florida shelf (WFS) is unusual in that it is cut off at its southern end by the Florida Keys, and in the north the orientation of the coast changes by 90° at the junction of the Florida Peninsula and the Florida Panhandle. While currents on the central and southern parts of the WFS have been measured for more than a decade and much has been learned [see the summary by Weisberg et al. (2005), (2009)], the only published in situ Eulerian records in the Florida Big Bend are the comparatively short records at K-Tower, an Air Force navigational tower in 19 m of water about 33 km south of the Big Bend coast (Fig. 1). Summer currents there (31 days, 15 August–15 September 1978) were reported at 4- and 8-m above the bottom by Marmorino (1983a); winter currents (1-m above the bottom in 1989/90 and 1990/91, and 12-m above the bottom in 1991/92) were reported by Weatherly and Thistle (1997). Both papers indicate that the substantial bend in the coastline makes the area of particular dynamical interest since the subinertial along-shelf wind stress is not in a simple local frictional balance with the subinertial along-shelf current, and no clear-cut relationships exist (Marmorino 1983a).

Fig. 1.

WFS with locations of current mooring sites (A, B, K-Tower, and S). Triangles represent NDBC buoys. The Big Bend coast extends around Apalachee Bay from Apalachicola in the west to the end of the eastern “arm” of Apalachee Bay approximately at the point marked as EEAB on the map.

Fig. 1.

WFS with locations of current mooring sites (A, B, K-Tower, and S). Triangles represent NDBC buoys. The Big Bend coast extends around Apalachee Bay from Apalachicola in the west to the end of the eastern “arm” of Apalachee Bay approximately at the point marked as EEAB on the map.

Utilizing new multiyear acoustic Doppler current profiler (ADCP) high-resolution current measurements, we investigate the dynamics of the subinertial flow at four locations near the Big Bend. Section 2 gives an overview of observations and data processing, including a brief description of the low-pass filter used to obtain the “subinertial” data to be analyzed. Most of the subinertial (in our data periodicity longer than a few days) energy is in the weatherband (periodicity from a few days to a few weeks), so our analysis of the subinertial data in sections 37 is essentially an analysis of the weatherband variability. Seasonal flows, typically with a variance of about 15% of the total subinertial variance, are treated separately in section 8. Coordinate systems for each site are analyzed in section 3. Vertical structure and flow strength for both along- and cross-isobath subinertial flow are described in section 4. The dynamics of the along-isobath flow at 19-m sites S and K-Tower and near-shore sites B and A are analyzed in sections 5 and 6, respectively. Section 7 contains a discussion of the subinertial across-isobath flow, section 8 the seasonal flow, and the concluding remarks are given in section 9.

2. Data

Observations used to investigate the dynamics of the Big Bend region's subinertial circulation include current, wind stress, sea level, and hydrographic data. These are described below.

a. Currents

As part of a state-funded north Florida red tide monitoring program, current measurements using a bottom-mounted, upward-looking Teledyne RD Instruments (RDI) Workhorse 300-kHz ADCP were begun on 19 January 2007 near K-Tower, an Air Force navigation tower in 19 m of water about 33 km south of the north Florida Big Bend coast (see map in Fig. 1, location as latitude and longitude coordinates in Table 1, and timeline of measurements in Fig. 2). Current velocity measurements are ongoing and from 3- to 15-m above the bottom with 1-m vertical resolution.

Table 1.

Mooring locations (lat, lon), their depths (m), and principal along-isobath directions (θ, counterclockwise from east) for the subinertial depth-averaged flow.

Mooring locations (lat, lon), their depths (m), and principal along-isobath directions (θ, counterclockwise from east) for the subinertial depth-averaged flow.
Mooring locations (lat, lon), their depths (m), and principal along-isobath directions (θ, counterclockwise from east) for the subinertial depth-averaged flow.
Fig. 2.

Timeline of moored ADCP measurements. Crosses indicate available hydrographic measurements along the K-Tower section.

Fig. 2.

Timeline of moored ADCP measurements. Crosses indicate available hydrographic measurements along the K-Tower section.

The red tide monitoring program ended in 2009, but in 2008 funding from the Northern Gulf of Mexico Institute (NGI) became available so that not only were the K-Tower measurements continued, but additional measurements were taken at two sites A and B inshore of K-Tower along a line approximately perpendicular to the coast (Fig. 1). At both site A (5-m depth, 6 km from the Big Bend coast, 11 March 2008–present) and site B (10-m depth, 15 km from the Big Bend coast, 19 June 2008–16 June 2009 and 6 July 2010–present) bottom-mounted, upward-looking Nortek 1-MHz acoustic wave and current (AWAC) profilers were deployed. The current measurements were made with a 0.5-m vertical resolution at depths from 1- to 3-m above the bottom at site A and from 1- to 7-m above the bottom at site B.

Finally, under funding from the red tide monitoring project, another bottom-mounted, upward-looking AWAC profiler was deployed at site S, about 45 km south of K-Tower and 70 km from the Big Bend coast in a water depth of 19 m, the same depth as at K-Tower. The first deployment (23 April–17 November 2009) measured currents from 1- to 15-m the bottom with 1-m vertical resolution, while the second deployment (17 November 2009–9 July 2010) had a 0.5-m vertical resolution.

Separate velocity measurements in the bottom log-layer were made by two Falmouth Scientific, Inc., two-dimensional acoustic current meters (FSI 2D-ACM) 25- and 85-cm above the bottom at K-Tower for several time intervals in 2007/08 and at site S for both deployment periods. However, at site S the FSI instruments failed on the second deployment, so no log-layer results are available then.

b. Wind

Meteorological measurements are available at K-Tower and two nearby National Data Buoy Center (NDBC) (http://www.ndbc.noaa.gov) buoys: 42036 northwest of Tampa, Florida, and 42039 southeast of Pensacola, Florida (Fig. 1).

c. Hydrography

Since 14 November 2006, approximately monthly (see the timeline in Fig. 2) hydrographic measurements have been made at five locations along a section from the Florida State University Coastal Marine Laboratory (FSUCML) to K-Tower. These measurements were typically taken at 0.5-m resolution and to 1 m from the bottom and 1 m from the surface. Also, hourly temperature and conductivity are available at K-Tower at 3- and 9-m above bottom since 19 December 2007.

d. Coastal sea level and atmospheric pressure

National Ocean Service/Center for Operational Oceanographic Products and Services (NOS/CO-OPS) (http://tidesandcurrents.noaa.gov/) provides 6-min coastal sea level and atmospheric pressure measurements at various locations along the WFS. Near the current mooring locations, they are at Apalachicola on the Big Bend coast (station 728690) and at Cedar Key on the Florida Peninsula coast (station 8727520). Similar data were also available from the closest station to the current sites, the NDBC station Shell Point, Florida (SHPF1), owned and maintained by the University of South Florida.

e. Data processing

All current velocity time series were checked for gaps and bad data, and long-period tidal variability (lunar fortnightly and lunar monthly) was removed via a least squares fit. To isolate the subinertial variability, the time series were low-pass filtered using a cosine–Lanczos filter (Emery and Thomson 2001) that passes 50% power at frequency 2π/40 h and 10% power at 2π/30 h. The time series filtered in this way are here called subinertial or low frequency interchangeably. Since near-surface contaminated (side lobe) current data were removed and not available to us, for depth-averaged calculations, which require an integral to the surface, we approximated the near-surface flow using the topmost good current value. All other analyses were based on a nonextrapolated record.

The sea level time series were adjusted for atmospheric pressure and filtered in the same way as those for the currents. The wind stress components were calculated from hourly wind speed and wind direction time series following Large and Pond (1982) and then low-pass filtered in the same manner as the currents. Since the wind stress components at the offshore NDBC buoys have high correlation and nearly unit regression coefficients (on average, r = 0.92, r95% = 0.06, and the regression coefficient is 0.97), we use the NDBC buoy 42039 measurements to represent the regional large-scale winds. The near-shore winds at K-Tower are, in general, weaker than the offshore winds, so we use the K-Tower wind record to illustrate the local wind effects near the Big Bend.

Whenever mentioned, correlations at the 95% confidence level were calculated following Ebisuzaki (1997), and all the presented correlations are significant at the 95% confidence level. With regard to regression coefficients, when two variables X and Y in a linear regression both contain “noise,” the regression of Y on X is not the reciprocal of the regression of X on Y. When the relative size of that noise is not known, the appropriate unbiased regression coefficient is the ratio of their standard deviations (Clarke and Van Gorder 2013). Since the measured physical quantities here all are contaminated by noise, often of uncertain amplitude, we will use this regression coefficient.

3. Coordinate system for the subinertial flow

The shelf bathymetry in the region is complex, and the isobaths consequently vary irregularly on short spatial scales (see, e.g., Fig. 3). Theoretically, in the absence of friction, by the conservation of potential vorticity in shallow water, flow should approximately follow the isobaths at subinertial frequencies and at “large” spatial scales. But does that mean that the low-frequency flow should follow the highly irregular isobaths in Fig. 3 or some larger-scale topographic trend? At what scales, dynamically, should we expect the flow to follow the isobaths?

Fig. 3.

(a) Depth (m) in a 5-km square centered on site B based on the 3-arcsec (~90-m horizontal resolution) U.S. Coastal Relief Model. Site B is marked by the star. (b) Bottom topography found from the least squares fit based on (1). In this case the along-isobath direction from (1) is 27° north of east, while the principal axis direction (Fig. 4) is 1° north of east.

Fig. 3.

(a) Depth (m) in a 5-km square centered on site B based on the 3-arcsec (~90-m horizontal resolution) U.S. Coastal Relief Model. Site B is marked by the star. (b) Bottom topography found from the least squares fit based on (1). In this case the along-isobath direction from (1) is 27° north of east, while the principal axis direction (Fig. 4) is 1° north of east.

For the flow to approximately follow the isobaths, the relative vorticity ζ should be small compared to the local Coriolis parameter f, for then, by the conservation of potential vorticity , the low-frequency flow will follow f/h and, hence, locally the depth h. For a flow following the isobaths, the relative vorticity depends on horizontal velocity shear and curvature vorticity , where is the depth-averaged along-isobath flow and R is the local radius of curvature of the isobath. Since the velocity shear is small compared to f, the flow will tend to follow the isobaths provided is small, that is, for isobaths with radius of curvature R. Mean flows are weak in the Big Bend region, and the subinertial flows have an amplitude of about 10 cm s−1. Since in the Big Bend f ≈ 7 × 10−5 s−1, R must have a scale much greater than km for low-frequency flows to remain approximately on the isobaths.

The above theoretical ideas were checked by first calculating the principal axes of the depth-averaged subinertial flow at the four measurement sites A, B, K-Tower, and S (Table 1). At each of the four measurement sites (see Fig. 4) the y axis is defined to lie along the principal axis such that its eastward component is positive. Consequently, the x axis in this right-handed system points offshore.

Fig. 4.

Ellipses showing principal axes of variance of the low-frequency currents at each of the four ADCP moorings in the Big Bend region. The positive along-isobath direction corresponding to the positive y axis is denoted by the arrows inside ellipses. In each case the length of the arrows is equal to the standard deviation and for scale it is 6 cm s−1 at K-Tower. The positive x axis points offshore at all sites. The positive component of the wind stress along the Florida peninsula is shown by the large arrow; is the positive component of the along-Bend wind stress, perpendicular to .

Fig. 4.

Ellipses showing principal axes of variance of the low-frequency currents at each of the four ADCP moorings in the Big Bend region. The positive along-isobath direction corresponding to the positive y axis is denoted by the arrows inside ellipses. In each case the length of the arrows is equal to the standard deviation and for scale it is 6 cm s−1 at K-Tower. The positive x axis points offshore at all sites. The positive component of the wind stress along the Florida peninsula is shown by the large arrow; is the positive component of the along-Bend wind stress, perpendicular to .

To see whether the y axis as defined above is really approximately “along isobath” at the appropriate topographic scales, we analyzed the 3-arcsec (~90-m resolution) bathymetric data provided by the National Geophysical Data Center (http://www.ngdc.noaa.gov/mgg/coastal/crm.html). At each of the four measurement sites the topographic data in a latitude–longitude square box, centered on the particular site, was approximated by a least squares fit to the linearly sloped topography:

 
formula

where x* (y*) are eastward (northward) coordinates relative to the box center. The resulting constant topographic gradient αe1 + βe2 (e1 = eastward unit vector, e2 = northward unit vector) is perpendicular to the unit vector (βe1αe2)/(α2 + β2)1/2 in the along-isobath direction. Squares with sides of lengths L ranging from 1 to 35 km were used to estimate “along isobath ” directions at various scales.

Three chords of length Rcurv can approximately describe the perimeter of a semicircle of radius Rcurv and length πRcurv ≈ 3Rcurv, but fewer than three are inadequate. This indicates that the straight isobaths in the squares with sides of length L above can approximately describe curves with radius of curvature L, but no smaller, that is, RcurvL. Figure 5a shows the along-isobath direction as a function of L at site B. For L from 1 to 10 km this direction, measured as degrees north of due east, changes considerably owing to the irregular nature of the topography. In this range of L, the along-isobath direction at each L is indicative of isobaths with radius of curvature approximately equal to that L. For L from about 10 to 35 km the along-isobath direction does not change, suggesting that the isobaths in this direction have a radius of curvature of at least 35 km.

Fig. 5.

(a) The along-isobath direction , measured (°) counterclockwise from east, at site B, being determined from various square boxes of size (see text). (b) The angular difference (°) between the major axis of the flow and the along-isobath direction as a function of for site A (thin dashed line), site B (thick line), K-Tower (thick dashed line), and site S (thin line). Negative δθ corresponds to the current major axis being rotated to the left of the isobath direction.

Fig. 5.

(a) The along-isobath direction , measured (°) counterclockwise from east, at site B, being determined from various square boxes of size (see text). (b) The angular difference (°) between the major axis of the flow and the along-isobath direction as a function of for site A (thin dashed line), site B (thick line), K-Tower (thick dashed line), and site S (thin line). Negative δθ corresponds to the current major axis being rotated to the left of the isobath direction.

From the small relative vorticity constraint discussed earlier, we expect the depth-averaged flow to follow the isobath for radius of curvature Rcurv 1.4 km. The result in Fig. 5a, therefore, suggests that the angular difference δθ between the along-isobath direction and the major axis of the low-frequency flow (see Fig. 3) should be small for L ≫ 1.4 km.

Figure 5b shows plots of δθ as a function of L at each of the sites, negative δθ corresponding to the current major axis being rotated to the left of the isobath direction. Plots at A, B, and K-Tower all show small slightly positive for L between 4 and 8 km, qualitatively consistent with the expected small δθ for L ≫ 1.4 km. For larger L, δθ remains small at K-Tower and site B, but at site A δθ increases to about 40°. This may be due to larger-scale topography not being indicative of more local variations that are large enough scale to cause along-isobath flow. More likely, at least at times of strong wind forcing, is that frictional effects are very strong in the very shallow (5-m depth) water at site A and play a fundamental role in the dynamics (see section 6). When frictional effects are dominant we do not expect the low-frequency flow to follow the isobaths. Unlike the results at the other three sites, at site S δθ is comparatively large in magnitude until box sizes increase to L ≈ 30 km. This may be due to the almost constant depth topography near site S that makes the estimation of accurate topographic gradients difficult.

4. Spatial structure and strength of the subinertial flow

The low-frequency wind-driven along-isobath flow on this wide shelf is expected to be barotropic (Clarke and Brink 1985; Mitchum and Clarke 1986b). The vertical profiles of the first mode empirical orthogonal function (EOF) for the along-isobath flow at K-Tower in all four seasons are shown in Fig. 6b. The first mode EOF explains about 90% of the variance of the along-isobath flow in each case. The profiles are approximately independent of depth except that the strength of the flow decreases toward the bottom over a depth of about 8–9 m or so. Such a decrease because of the bottom friction over a vertical scale of about this size is expected based on previous estimates of the vertical turbulent frictional scale in this region (Marmorino 1983b).

Fig. 6.

Vertical structure of the first mode EOF for the subinertial (a) across-isobath and (b) along-isobath flow at K-Tower in winter (thick solid line), spring (thin solid line), summer (thick dashed line), and fall (thin dashed line).The percentages in the legend represent the variance explained by the first mode EOF in each season at K-Tower.

Fig. 6.

Vertical structure of the first mode EOF for the subinertial (a) across-isobath and (b) along-isobath flow at K-Tower in winter (thick solid line), spring (thin solid line), summer (thick dashed line), and fall (thin dashed line).The percentages in the legend represent the variance explained by the first mode EOF in each season at K-Tower.

The winter profile also shows a slight decrease of the flow near the surface, consistent with the vertical scale of the surface turbulent frictional layer. This decrease can be associated with the local surface Ekman flow in the direction opposite to the main barotropic along-isobath flow. This effect (see Fig. 7) is most noticeable in the stormy El Niño winter 2009/10. In that winter, the much stronger local cross-isobath wind stress drove an along-isobath transport that weakened the flow amplitude in the surface frictional layer. Figure 7 shows that the removal of the Ekman part of the flow near the surface makes the along-isobath flow approximately independent of depth above the frictional bottom layer. The along-isobath flow in all four seasons is of similar strength, about 8 cm s−1 (Fig. 6b). Note that for all the EOFs the principal components have been normalized so that their variance is 0.5, enabling the EOF vertical profiles to be representative of the flow amplitudes.

Fig. 7.

Vertical structure (thin line) of the first mode EOF for the subinertial along-isobath flow at K-Tower in the El Niño winter 2009/10 and the corresponding EOF (thick line with dots) of the along-isobath flow with the locally forced Ekman flow component removed. The Ekman flow was calculated using the local wind stress at K-Tower with a constant Ekman depth δ = 12 m. The percentages in the legend represent the variance explained by the first mode EOF in both cases.

Fig. 7.

Vertical structure (thin line) of the first mode EOF for the subinertial along-isobath flow at K-Tower in the El Niño winter 2009/10 and the corresponding EOF (thick line with dots) of the along-isobath flow with the locally forced Ekman flow component removed. The Ekman flow was calculated using the local wind stress at K-Tower with a constant Ekman depth δ = 12 m. The percentages in the legend represent the variance explained by the first mode EOF in both cases.

The first EOF of the cross-isobath profiles at K-Tower in Fig. 6a explains most of the variance in each season, but the variance explained is smaller than for the along-isobath case. This may be due to a greater percentage of noise expected in the smaller cross-isobath signal. It may also have to do with the nonlinearity of the cross-isobath flow response, which will be discussed later in section 7a. The vertical structure of the across-isobath flow is such that the depth-averaged across-isobath current is much smaller than the depth-averaged along-isobath current, in keeping with the depth-averaged flow being approximately along the isobath (see section 3).

Figure 8b shows first mode EOF along-isobath vertical structures for all four current measurement sites during all the times that the measurements were taken at each site. Results for the along-isobath flow in the same 19 m of water depth at sites S and K-Tower are similar, but at the shallower sites A and B the velocity is more sheared. Such shear is expected in shallower water where the flow is almost entirely in the turbulent bottom boundary layer. This is discussed further in section 6.

Fig. 8.

The vertical structure of the first mode EOF for the subinertial (a) across-isobath and (b) along-isobath flow at site S (thin line, open circles), K-Tower (thin line, solid circles), site B (thick line, open circles), and site A (thick line, solid circles). The percentages in the legend represent the variance explained by the first mode EOF at each site.

Fig. 8.

The vertical structure of the first mode EOF for the subinertial (a) across-isobath and (b) along-isobath flow at site S (thin line, open circles), K-Tower (thin line, solid circles), site B (thick line, open circles), and site A (thick line, solid circles). The percentages in the legend represent the variance explained by the first mode EOF at each site.

The cross-isobath first mode EOF vertical structures at all four sites are shown in Fig. 8a. Analogously to Fig. 6a, the vertical structure of the across-isobath flow at each site is such that the depth-averaged across-isobath current is much smaller than the depth-averaged along-isobath current. The variance explained by the across-isobath vertical EOF structures is only about 60% and, as noted above, may not be an adequate representation of the across-isobath flow.

At each mooring site the along-isobath vertical profile of the first mode EOF does not change sign with depth and explains about 90% of the variance. While the cross-isobath flow u at some sites is not of opposite sign near the surface and bottom, possibly because of the strongly varying topography alongshore or to the direction of our axes being slightly in error, it is still true that is comparatively small to . Based on these results, in the next section we will use the depth-averaged along-isobath subinertial flow as a representative of the along-isobath subinertial flow.

5. Along-isobath flow dynamics in 19-m water at sites K-Tower and S

According to coastally trapped wave (CTW) theory (see, e.g., Gill and Schumann 1974; Gill and Clarke 1974; Clarke 1977), seaward of an “inner shelf” region where surface and bottom Ekman layers overlap (Mitchum and Clarke 1986a), subinertial along-isobath flow is found by integrating the alongshore component of the wind stress along characteristics corresponding to CTW modes (Mitchum and Clarke 1986b). Since the dominant first CTW mode propagates from the Florida Keys to the Big Bend in a day or so, a time much shorter than subinertial periodicity, to a first approximation for the subinertial time series of interest, the wave propagation speed is effectively infinite. This implies that the dominant first mode characteristic integral reduces to a simple integral of the alongshore component of the wind stress from the Florida Keys to the Big Bend. Since the low-frequency wind stress is of large spatial scale, dynamically we would expect the along-isobath wind-driven flow to be more highly correlated with wind stress in the along-shelf direction of the WFS (see the arrow in Fig. 4), rather than the local along-isobath direction. Thus, even though the along-isobath direction at K-Tower is close to the direction of (see Fig. 4), we expect that , the depth-averaged along-isobath flow at K-Tower, should be more highly correlated with than . Figures 9a and 9b illustrate that this, indeed, is the case for the winter 2009/10, and Table 2 shows that is more highly correlated with than with for all seasons of the year. Correlations of with are highest in winter and lowest in summer, the season when the subinertial is weakest. The correlation is the highest when lags by about 16 h, a result expected from previous analyses (Mitchum and Clarke 1986a; Liu and Weisberg 2005a) and discussed later below.

Fig. 9.

(a) The winter 2009/10 along-isobath depth-averaged subinertial flow at K-Tower (solid line) and (dashed line). The correlation between the time series is rmax = 0.84 when the current lags the wind stress by 16 h. (b) As in (a), but for replaced by (dashed line), the local along-isobath wind stress at K-Tower. In this case, the correlation is insignificant at zero lag and rmax = 0.35 when the current lags the wind stress by 30 h. (c) As in (a), but for replaced by , the subinertial depth-averaged along-isobath flow at site S. The correlation is rmax = 0.95 when lags by 1 h. In the figure, is shifted by (a) 16 h, (b) 30 h, and (c) 1 h to the left to illustrate the high correlations.

Fig. 9.

(a) The winter 2009/10 along-isobath depth-averaged subinertial flow at K-Tower (solid line) and (dashed line). The correlation between the time series is rmax = 0.84 when the current lags the wind stress by 16 h. (b) As in (a), but for replaced by (dashed line), the local along-isobath wind stress at K-Tower. In this case, the correlation is insignificant at zero lag and rmax = 0.35 when the current lags the wind stress by 30 h. (c) As in (a), but for replaced by , the subinertial depth-averaged along-isobath flow at site S. The correlation is rmax = 0.95 when lags by 1 h. In the figure, is shifted by (a) 16 h, (b) 30 h, and (c) 1 h to the left to illustrate the high correlations.

Table 2.

Maximum correlation of with and and the corresponding time (h) that lags the wind stress for each season of the year.

Maximum correlation of  with  and  and the corresponding time (h) that  lags the wind stress for each season of the year.
Maximum correlation of  with  and  and the corresponding time (h) that  lags the wind stress for each season of the year.

A referee wondered whether the depth-averaged along-isobath flow at K-Tower could be driven by the local cross-isobath wind stress there since this is in the same direction as . But, while subinertial cross-isobath wind stress can affect coastal sea level and cross-isobath flow (see, e.g., Tilburg 2003), its effect on depth-averaged along-isobath flow is small compared to the same strength along-isobath wind [e.g., compare the term proportional to υ in Figs. 7a,b and 8a,b in Tilburg (2003)]. Furthermore, as we have seen earlier in the second paragraph of section 4, the flow generated by the cross-shelf forcing is opposite to the observed along-isobath flow.

Site S is approximately on the same 19-m isobath as K-Tower and, compared to the length of the Florida Peninsula, is only a short distance from it (see Fig. 1). Consequently the flow at K-Tower and site S should be forced by essentially the same integral of the wind stress along the coast from the Florida Keys. According to CTW theory, the depth-averaged alongshore flow at site S () and K-Tower () should therefore be very similar and they are (Fig. 9c). The maximum winter 2009/10 correlation coefficient rmax = 0.95 is when lags by 1 h, but the correlation is nearly the same (r = 0.94) when there is no lag. Figure 9c also shows that the flow amplitudes are essentially the same, at least for winter 2009/10. Correlation and regression results for the site S record indicate (Table 3) that and closely approximate each other for the other seasons of the year, the agreement again being lower in the summer when is weakest.

Table 3.

Maximum correlation of and , the corresponding lag (h), and the ratio of the standard deviations as a function of the season of the year. Correlations at zero lag are shown in parentheses. Note that the K-Tower and site S measurement dates only overlap from 23 Apr 2009 to 9 Jul 2010, so most of the results for each season are for a single year.

Maximum correlation of  and , the corresponding lag (h), and the ratio  of the standard deviations as a function of the season of the year. Correlations at zero lag are shown in parentheses. Note that the K-Tower and site S measurement dates only overlap from 23 Apr 2009 to 9 Jul 2010, so most of the results for each season are for a single year.
Maximum correlation of  and , the corresponding lag (h), and the ratio  of the standard deviations as a function of the season of the year. Correlations at zero lag are shown in parentheses. Note that the K-Tower and site S measurement dates only overlap from 23 Apr 2009 to 9 Jul 2010, so most of the results for each season are for a single year.

Earlier in this section, we found that lags by about 16 h. Since , we can establish the reason for this lag if we can establish why lags by about 16 h. In the remainder of this section, we investigate why such a lag might arise.

Consider the linearized depth-averaged along-isobath momentum equation

 
formula

where the overbar denotes depth average, t is time, ρ* the mean water density, and are, respectively, the wind stress and the bottom stress in the along-isobath direction. Based on a theoretical analysis, Mitchum and Clarke (1986a) suggested that (2) can be approximated, at 19-m depth, by

 
formula

In deriving (3) was assumed to be negligible and the pressure barotropic, so that with as the sea level corrected for the effect of atmospheric pressure. In addition, the along-isobath bottom stress was represented as

 
formula

In 19-m depth

 
formula

with δ being the e-folding decay scale for the surface and bottom Ekman layers.

At the southern “end” of the WFS the normal and tangential coordinate system that we have chosen is severely contorted, isobaths heading westward along the northern side of the Keys and then back eastward again on the southern side of the Keys to join with isobaths on the eastern coast of the United States. Mitchum and Clarke (1986b) recognized that it would be difficult for energy to propagate from the southern side of the Keys, around their end, and enter the WFS. This is especially so given the existence of the very narrow shelf and strong northward Florida Current south of the Keys. Consistent with this difficulty, sea level at Key West is much smaller than coastal sea levels further to the north [see, e.g., Fig. 2 of Marmorino (1982)], and Mitchum and Clarke (1986b) found that the essential large-scale dynamics of the low-frequency variability on the WFS could be described by putting η = 0 at the WFS southern end. Thus the WFS can be regarded, approximately, as a broad shelf with northward/northwestward isobaths “ending” at the Keys where η = 0.

Note that, by geostrophy, η = 0 across the southern WFS “boundary” marked by the Keys corresponds, as far as the WFS is concerned, to = 0 there. Consequently, we expect from (3) that near the Keys

 
formula

This is consistent with Mitchum and Clarke (1986b), their (4.2) and (4.5a,b), for small y. Farther to the north, CTW theory (Mitchum and Clarke 1986b) shows that these terms no longer exactly balance, and the imbalance results in a nonzero according to (3). The alongshore sea level gradient, resulting from the “cut off” shelf at the Florida Keys, thus acts as a “brake” on the wind stress forcing and weakens . Cancellation of by y is consistent with the results of Liu and Weisberg (2005a) and the observed and calculated increasing coastal sea level amplitudes northward of the Florida Keys by CTW theory (Mitchum and Clarke 1986b).

The solution of (3) is

 
formula

so the initial condition is unimportant after times more than about twice the frictional spin down time h/R. Note that (7) predicts that lags the forcing F, which, as we have seen, is proportional to a reduced . For low enough frequency forcing the lag is approximately h/R. Since lags by about 16 h (see Table 2), we expect h/R ~16 h.

Mitchum and Clarke (1986b) tested (3) using a short current meter record off Cedar Key (see Fig. 1) in 21 m of water with measured wind stress and estimated from coastal sea levels at Cedar Key and St. Petersburg. Good agreement was obtained with δ = 8.5 m and, hence, by (5) with Using a much more extensive dataset off Sarasota (see Fig. 1), Liu and Weisberg (2005a) verified that the along-shelf momentum balance (2) could be approximated by (3) with The balance (3) has also been checked on other continental shelves in similar water depths with similar R [e.g., off California by Lentz and Winant (1986) and Hickey et al. (2003)].

We tested whether the above physics also applies at site S. As was done for the WFS by Mitchum and Clarke (1986a) and Liu and Weisberg (2005a), we used coastal sea level to estimate ηy at the shallow water site, in the present case writing

 
formula

with Δη the sea level at Cedar Key minus that at Shell Point and Δy = 170 km, the alongshore distance between these stations (see Fig. 1). Liu and Weisberg accounted for the possible difference between ηy at the coast and ηy in 15 m of water by multiplying Δηy by a factor μ = 0.7, and here we do the same.

The bottom friction parameter R needed for the calculation at site S can be obtained from (4) by regressing onto at site S, the bottom stress being calculated from the two log-layer bottom boundary layer FSI current measurements (see section 2a) at heights ζ1 = 25- and ζ2 = 85-cm above the bottom. This calculation proceeds in standard fashion as follows. In the logarithmic layer the direction of the stress is the same as the direction of the flow, and the speed of the flow U is a function of the height ζ above the bottom according to

 
formula

where , κ is von Kármán's constant, and ζ0 is the roughness length. From (9) it follows that

 
formula

and, hence, that |τ| can be estimated as

 
formula

Since |τ| and the direction of τ are known for the subinertial time series, can be calculated. Based on (4), regression of on at site S gave for the period 23 April–17 November 2009. A similar value () was obtained at K-Tower based on several measurement periods in 2007/08. From (5) and , for , δ ≈ 17 m, about double a previous estimate of 8.5 m by Marmorino (1983b).

We compared the theoretical estimate for from (7) with the observed using the log-layer R estimate and μηy(t) based on (8) with μ = 0.7 as explained above. The theoretical and observed time series were well correlated (rmax = 0.6 when the observed flow lags the model by 6 h) and had similar amplitude (regression coefficient = 0.89). The correlation was improved and the lag reduced if we chose smaller μ = 0.3–0.5 for R = 4.5–6 (× 10−4 m s−1) (Fig. 10a). This value of R corresponds to δ = 12.8–17 m. Figure 10b suggests that, even as far distant from the Keys as site S, the along-isobath pressure gradient term is acting as an O(1) brake on the flow. In reporting this result we recognize that the estimate of ηy at S in 19 m is crude since we use a finite difference of coastal sea level, one of the sea level stations (Shell Point) being in the topographically complex region near the Big Bend (Fig. 1). Nevertheless, the O(1) contribution made by the alongshore pressure gradient estimate still permits good agreement between the measured and modeled υ, suggesting that the pressure gradient estimate has some validity.

Fig. 10.

(a) The winter 2009/10 depth-averaged along-isobath flow at site S (solid line) and the flow modeled by (7) with and μ = 0.5 (dashed line). The correlation coefficient rmax = 0.7 when the observed flow lags the modeled flow by 2 h. In that case, the regression coefficient = 0.9. (b) υmodeled as in (7) with (dashed) and without (solid) the alongshore pressure gradient “brake.” As expected the modeled υ without the brake is larger, with rms υ (no brake) = 14.7 cm s−1 and rms υ (brake) = 9.2 cm s−1, giving a ratio of 1.6. Note that the velocity scale differs in (b) and the brake (dashed model time series) is the same in both (a) and (b).

Fig. 10.

(a) The winter 2009/10 depth-averaged along-isobath flow at site S (solid line) and the flow modeled by (7) with and μ = 0.5 (dashed line). The correlation coefficient rmax = 0.7 when the observed flow lags the modeled flow by 2 h. In that case, the regression coefficient = 0.9. (b) υmodeled as in (7) with (dashed) and without (solid) the alongshore pressure gradient “brake.” As expected the modeled υ without the brake is larger, with rms υ (no brake) = 14.7 cm s−1 and rms υ (brake) = 9.2 cm s−1, giving a ratio of 1.6. Note that the velocity scale differs in (b) and the brake (dashed model time series) is the same in both (a) and (b).

Another source of model error is the neglect of the terms in (2) to get (3). The term may not be small. However, inclusion of this term into the forcing in (3) did not improve the modeled result, probably due to the difficulty in estimating when the instruments do not measure a part of the water column.

6. Along-isobath inner-shelf flow at sites A and B

Since an average estimated e-folding scale for the Ekman depth is ~8.5 m or more in the region [see section 5 and Marmorino (1983b)], it is likely that at site A (water depth 5 m) and site B (water depth 10 m) the surface and bottom Ekman layers will overlap. Equation (2) suggests that, as the coast is approached and the water depth , the surface and the bottom stress must balance; if they did not, the stress divergence force would approach infinity, and the flow would become very large. The idea that the turbulent stress becomes constant and equal to the wind stress as is consistent with the overlapping Ekman layer shallow-water theory of Mitchum and Clarke (1986a). As pointed out by Mitchum and Clarke, this result means that the currents in very shallow water are driven by the local wind stress. This is quite different from the currents at K-Tower and site S, which are driven remotely by an integration of the alongshore wind stress along the WFS from the Florida Keys.

There is some evidence that the currents at the 5-m site A are driven by local rather than remote forcing, especially in the winter when the forcing is strongest. At site A the major axis of the depth-averaged flow is at −30° (Fig. 4), that is, 30° south of east. The largest correlation of with different wind stress components in all directions occurs when the wind stress angle is about −20° (Table 4), which is much closer to the major axis of the flow than the −60° orientation of , appropriate for remotely forced flow.

Table 4.

Maximum correlations of the subinertial depth-averaged along-isobath flow and the subinertial wind stress in winter, the time lag (h) at which the flow follows the wind stress, and the direction of the wind stress (counterclockwise from east) that provides the maximum correlation.

Maximum correlations of the subinertial depth-averaged along-isobath flow and the subinertial wind stress in winter, the time lag (h) at which the flow follows the wind stress, and the direction of the wind stress (counterclockwise from east) that provides the maximum correlation.
Maximum correlations of the subinertial depth-averaged along-isobath flow and the subinertial wind stress in winter, the time lag (h) at which the flow follows the wind stress, and the direction of the wind stress (counterclockwise from east) that provides the maximum correlation.

Since the flow over the whole depth is in a constant stress layer as , in that limit for an eddy viscosity formulation for the stress we have

 
formula

where A is the constant eddy viscosity. Integrating (12) from the bottom, where υ = 0, to some general z gives the linear profile

 
formula

This is consistent with the Mitchum and Clarke (1986a) results when .

We tested (13), and Fig. 11 summarizes these results by showing the depth-averaged correlations between υ and the local along-isobath wind stress at site A, as well as the e-folding scale δ for all calendar months when the correlations are significant. The average δ = 8–9 m is comparable to the 8.5 m value found by Marmorino (1983b) using a different analysis and data. The Ekman e-folding scale δ is smaller in the summer, consistent with higher stratification and the weaker wind forcing resulting in lower turbulence then. The small depth theory (13) is invalid in the summer because it relies on the water depth to be less than about half of δ, and in the summer hδ (Fig. 11).

Fig. 11.

(a) The depth-averaged correlation between the subinertial υ(z, t) and at site A averaged by calendar month. (b) The depth-averaged e-folding scale calculated from (13) corresponding to the correlation calculations in (a).

Fig. 11.

(a) The depth-averaged correlation between the subinertial υ(z, t) and at site A averaged by calendar month. (b) The depth-averaged e-folding scale calculated from (13) corresponding to the correlation calculations in (a).

At site B the water depth is 10 m, comparable to, or larger than δ. Therefore, the constant stress dynamics of site A is not expected to be valid. More telling, however, is that the along-isobath component of the subinertial low-frequency depth-averaged flow responds best to the wind stress in the direction −60° (Table 2), or , rather than to the local along-isobath wind stress, indicating dynamics more like that at K-Tower than at site A.

7. Across-isobath flow

In section 7a, we consider the across-isobath flow in the frictional bottom boundary layer and in section 7b the frictional surface boundary layer.

a. Asymmetric near-bottom across-isobath flow

As we saw earlier in section 5, the subinertial along-isobath flow at K-Tower is, to a first approximation, remotely driven by . When is positive (southward), υ is positive (eastward) at K-Tower, and, when is negative, υ is negative. This can be seen in Fig. 12b, showing the typical along-isobath flows at K-Tower, site B, and site A when (thick lines) and (thin lines). The K-Tower profiles correspond to the longest lines, the site B profiles to the next longest, and site A profiles to the shortest as the depth decreases toward the coast. As noted in sections 5 and 6, the K-Tower profile is quasi barotropic, but the site A profile is strongly sheared because of bottom friction. Since is approximately parallel to the y axis at site A (see Fig. 4), we expect that the locally driven flow at site A would also have the same sign as , as Fig. 12b shows. Site B, being dynamically between K-Tower and site A but closer to K-Tower (see the end of section 6), also should have the same sign response as , which is so (Fig. 12b). Figure 12b indicates that υ for positive is slightly greater than υ for negative, and this is at least partly explained by being slightly larger in magnitude on average when it is positive than when it is negative (about 14 cPa compared to about −12 cPa).

Fig. 12.

The vertical subinertial (a) cross- and (b) along-isobath flow profiles corresponding to the extreme upwelling and the extreme downwelling events at the 19-m site K-Tower, 10-m site B, and 5-m site A off the WFS Big Bend coast. The extreme upwelling profile (thick solid) at each site is an average over all times when > 7 cPa, and, similarly, the extreme downwelling profile (thin solid) at each site is an average over all times when < −7 cPa. In the extreme upwelling case average = 14 cPa, and in the extreme downwelling case average = −12 cPa. Note that the local along-isobath wind stress component at site A, , is not significantly different from since the isobath orientation at site A is almost in the direction of the Florida Peninsula (see Table 1).

Fig. 12.

The vertical subinertial (a) cross- and (b) along-isobath flow profiles corresponding to the extreme upwelling and the extreme downwelling events at the 19-m site K-Tower, 10-m site B, and 5-m site A off the WFS Big Bend coast. The extreme upwelling profile (thick solid) at each site is an average over all times when > 7 cPa, and, similarly, the extreme downwelling profile (thin solid) at each site is an average over all times when < −7 cPa. In the extreme upwelling case average = 14 cPa, and in the extreme downwelling case average = −12 cPa. Note that the local along-isobath wind stress component at site A, , is not significantly different from since the isobath orientation at site A is almost in the direction of the Florida Peninsula (see Table 1).

Because of bottom friction, in standard fashion we expect the along-isobath flows shown in Fig. 12b to induce cross-isobath bottom boundary layer flow. Specifically, since υ is quasigeostrophic above the bottom boundary layer (Gill and Schumann 1974; Mitchum and Clarke 1986b; Liu and Weisberg 2005a), and since υ and, consequently, the Coriolis force weaken much more than the cross-isobath pressure gradient force in the bottom boundary layer, cross-isobath flow is induced in the bottom boundary layer. This flow should be shoreward (negative) when υ is positive and seaward (positive) when υ is negative. Figure 12 shows that this is observed for the two deeper sites where there is a definite bottom boundary layer; near the bottom of the water column the thick and thin υ curves in the lower panel correspond to thick and thin u curves of opposite sign in the upper panel. However, note that, while the υ fields in the lower panel are comparable in size, the u fields near the bottom differ by a factor of 4 or more and have less vertical shear.

Why should there be such a strong asymmetry in the u field? A similar flow asymmetry has been previously observed and explained by Weisberg et al. (2001) (see also Liu and Weisberg 2005b, 2007; Liu et al. 2006) for the WFS off central Florida. The Weisberg et al. explanation involved vertical stratification and no vertical mixing, but, in the Big Bend over the relevant lower half of the water column, the vertical density gradient essentially vanishes, and it is the horizontal density gradient that generally seems more important to the dynamics. The strength of the horizontal density gradients can be seen from hydrographic sections showing temperature, salinity, and density profiles (Fig. 13). Especially in the lower part of the water column in the deeper water, these profiles are strongly dependent on x and nearly independent of z. Seasonal horizontal density gradients are very large, mainly attributed to the terrestrial freshwater flux of lower density water (see the discussion in section 8b).

Fig. 13.

The vertical density, salinity, and temperature profiles from the coast to K-Tower on (a) 14 Dec 2009 and (b) 6 Nov 2007, corresponding to the typical property distributions in, respectively, the colder and wetter El Niño winter 2009/10 and the warmer and drier end of 2007/beginning of 2008. The density distribution in (b) is reversed over most of the section, with less dense water at K-Tower than that closer to the coast, including the hydrographic profile closest to K-Tower. In our calculations (see main text) the horizontal density gradient at K-Tower was calculated using the K-Tower profile and the profile closest to it (site 4).

Fig. 13.

The vertical density, salinity, and temperature profiles from the coast to K-Tower on (a) 14 Dec 2009 and (b) 6 Nov 2007, corresponding to the typical property distributions in, respectively, the colder and wetter El Niño winter 2009/10 and the warmer and drier end of 2007/beginning of 2008. The density distribution in (b) is reversed over most of the section, with less dense water at K-Tower than that closer to the coast, including the hydrographic profile closest to K-Tower. In our calculations (see main text) the horizontal density gradient at K-Tower was calculated using the K-Tower profile and the profile closest to it (site 4).

But why does this horizontal density gradient cause an asymmetry in the cross-shelf near-bottom flow? Consider an idealized case where the mean density is lower near the coast and independent of depth. By the standard boundary layer dynamics discussed earlier, a quasigeostrophic along-isobath flow induces a bottom boundary layer transport to the left of the flow in the Northern Hemisphere (Fig. 14). Since there is no mean vertical stratification initially, when υ < 0 and the bottom boundary layer flow is driven seaward by the cross-isobath pressure gradient (Fig. 14a), this immediately leads to less dense water under more dense water, a gravitational instability, and thus mixing. This spreads the seaward flow over an increased depth and weakens it. By contrast, in Fig. 14b, when the along-isobath flow is reversed, the induced shoreward flow leads to more dense water underlying less dense water and gravitational stability. Consequently, for a given alongshore flow speed, the induced near-bottom u field should be much stronger when the bottom boundary layer flow is toward rather than away from the coast. This is consistent with Fig. 12. When is positive the flow is favorable for upwelling and southward over the Florida Peninsula, the along-isobath flow is eastward (positive) in the Big Bend (Fig. 12a), and the bottom boundary layer velocity is large and shoreward (Fig. 12b). This shoreward transport is much larger than the seaward transport when is negative and the Big Bend near-bottom along-isobath flow is westward. A similar mixing asymmetry occurs over the northern California shelf (Lentz and Trowbridge 1991), although in that case the mechanism is associated with vertical stratification and a sloping bottom.

Fig. 14.

(a) Cartoon of the Big Bend along-isobath υ and induced cross-isobath u flows when is strongly negative, that is, has a northward component and, by CTW theory, remotely drives a westward (negative) along-isobath flow at K-Tower. This leads to a seaward bottom boundary layer flow and, because of the mean horizontal density gradient, a less dense boundary layer under more dense water, and, consequently, gravitational instability and mixing. (b) When is strongly negative and remotely drives an eastward alongshore flow at K-Tower, the shoreward bottom boundary layer flow is gravitationally stable, and vertical mixing does not impede the shoreward bottom boundary layer flow.

Fig. 14.

(a) Cartoon of the Big Bend along-isobath υ and induced cross-isobath u flows when is strongly negative, that is, has a northward component and, by CTW theory, remotely drives a westward (negative) along-isobath flow at K-Tower. This leads to a seaward bottom boundary layer flow and, because of the mean horizontal density gradient, a less dense boundary layer under more dense water, and, consequently, gravitational instability and mixing. (b) When is strongly negative and remotely drives an eastward alongshore flow at K-Tower, the shoreward bottom boundary layer flow is gravitationally stable, and vertical mixing does not impede the shoreward bottom boundary layer flow.

Sometimes, as in the bottom three panels in Fig. 13, the “mean” density gradient can be reversed. In this case, probably because of the 2007/08 La Niña, terrestrial conditions were drier, the salinity seaward gradient was greatly reduced, and from 13-m depth to K-Tower the colder near-shore temperatures reversed the horizontal density gradient. By the bottom boundary layer asymmetry mechanism, when the “mean” horizontal density gradient is reversed, the vertical structure of the cross-isobath boundary layer flow should change. Evidence for this is provided by the extreme upwelling case at K-Tower. For the usual case when density increases from the coast, the shoreward bottom boundary layer transport is gravitationally stable and strong (see Fig. 12; repeated in Fig. 15 as the Δρ > 0 case). But when the “mean” horizontal density gradient reverses (Δρ < 0 in Fig. 15), shoreward bottom boundary layer flow is gravitationally unstable, and the resultant observed flow is weaker and is not concentrated in a bottom boundary layer.

Fig. 15.

The vertical subinertial K-Tower along-isobath υ velocity profiles for the usual extreme upwelling case when the density gradient increases from the coast (thick solid, Δρ > 0) and when the density gradient decreases from the coast (thin solid, Δρ < 0). The thick solid curve is as in Fig. 12 and is the average velocity profile for all times when > 7 cPa, while the thin solid curve is the average over those times in November 2007 when > 7 cPa. The thick- and thin-dashed curves are analogously defined for the K-Tower cross-shelf u velocity profiles. Note that, consistent with the similar-sized thick and thin solid υ profiles, the average values of > 7 cPa in the two cases are similar [14 cPa (whole record) and 11 cPa (November 2007)].

Fig. 15.

The vertical subinertial K-Tower along-isobath υ velocity profiles for the usual extreme upwelling case when the density gradient increases from the coast (thick solid, Δρ > 0) and when the density gradient decreases from the coast (thin solid, Δρ < 0). The thick solid curve is as in Fig. 12 and is the average velocity profile for all times when > 7 cPa, while the thin solid curve is the average over those times in November 2007 when > 7 cPa. The thick- and thin-dashed curves are analogously defined for the K-Tower cross-shelf u velocity profiles. Note that, consistent with the similar-sized thick and thin solid υ profiles, the average values of > 7 cPa in the two cases are similar [14 cPa (whole record) and 11 cPa (November 2007)].

b. Near-surface across-isobath flow

We analyzed the near-surface across-isobath flow at K-Tower by considering the linearized along-isobath momentum equation averaged over a surface turbulent layer of depth D:

 
formula

In (14) τy(−D) is the turbulent stress in the y direction at depth D, and, as noted earlier, is the wind stress in the y direction. If were due to Ekman transport and if D were large enough so that τy(−D) were negligible compared to , then (14) would simplify to

 
formula

In that case would be entirely due to the local along-isobath wind stress.

We tested the simple local balance (15) using K-Tower wind stress and calculated from the current observations there. Figure 16 shows the winter 2009/10 results with D = 9 m, an appropriate depth given the structure of u in Fig. 6. The correlation between measured and predicted is r = 0.62, but Fig. 16 shows that the measured and predicted amplitudes do not agree, and, consistently, the regression coefficient is not unity.

Fig. 16.

The depth-averaged near-surface across-isobath subinertial flow at K-Tower in El Niño winter 2009/10 (solid line) and the modeled using (15) depth-averaged near-surface Ekman flow (dashed line). The depth averaging was done for D = 9 m below the surface. The correlation between the measured and the modeled flow is r = 0.62, and the regression coefficient is 1.3.

Fig. 16.

The depth-averaged near-surface across-isobath subinertial flow at K-Tower in El Niño winter 2009/10 (solid line) and the modeled using (15) depth-averaged near-surface Ekman flow (dashed line). The depth averaging was done for D = 9 m below the surface. The correlation between the measured and the modeled flow is r = 0.62, and the regression coefficient is 1.3.

Figure 11 shows that in winter δ ≈ 9–10 m, so Dδ. When D = δ, standard Ekman layer theory shows that τy(−D) is not completely negligible in (14), and

 
formula

Thus, the cross-isobath wind stress can contribute significantly to cross-isobath flow even when the surface flow is averaged over the e-folding depth δ. We modified the formula for in (15) using (16), but the results in Fig. 16 changed negligibly.

We also used the measured current data to calculate and, from (14), tested whether could be calculated from

 
formula

Again, there was negligible improvement compared to the results shown in Fig. 16.

According to (14), the only other term contributing to is the along-isobath pressure gradient contribution, −y/f. We had no along-isobath pressure or sea level measurements to estimate this term, but we tried to estimate it using a finite difference between the coastal sea levels at Shell Point and Apalachicola (see Fig. 4) and an adjustable scale factor to take into account the change in pressure gradient from the coast. Again, there was a negligible improvement in the Fig. 16 results. But we cannot rule out −gηy/f as a major contributor to since, in the topographically complex Big Bend region, it is likely that ηy at K-Tower is not accurately estimated from a finite difference of the coastal Apalachicola and Shell Point sea levels.

Other possible contributors to the measured Eulerian flow are the nonlinear terms omitted from (14) and subinertial contributions driven by subinertial changes in the size and direction of propagating surface gravity waves (see, e.g., Xu and Bowen 1994). Based on the coherence and similar size of the velocities at the B, K, and S sites in Fig. 4, the nonlinear terms are negligible. Calculations based on the surface wave data from the ADCP instrument at K-Tower suggest that wave-generated subinertial near-surface flows are also much smaller than . So, it seems that the alongshore pressure gradient forcing, which we could not estimate accurately, is the likely reason for the discrepancy in Fig. 16.

8. Seasonal and mean flow

As mentioned in the introduction, subinertial variability is dominated by the weatherband frequencies (periodicity from a few days to a few weeks). Although they are weaker, the lower-frequency seasonal flows are in the same direction for longer time intervals and so can often transport particles farther than the stronger higher-frequency flows. Because of this, seasonal and mean flows are of importance to the life cycles of some of Florida's commercially valuable fisheries like the gag grouper (see, e.g., Fitzhugh et al. 2005), red tide blooms (Carlson and Clarke 2009), and the transport of pollutants like oil spills.

Notwithstanding the importance of seasonal and mean flows, there have been few estimates of such flows in the Big Bend region. DiMarco et al. (2005) and Ohlmann and Niiler (2005) analyzed Lagrangian surface drifter current estimates for the entire northern Gulf of Mexico continental shelves and suggested that the mean and surface flows are comparatively small in the Big Bend region. On the other hand, Carlson and Clarke (2009) calculated geostrophic seasonal surface flow using TOPEX/Poseidon/Jason-1 along-track shelf-averaged seasonal surface flow near the Big Bend and estimated that seasonal shelf currents could change by ~20 cm s−1 over the calendar year. Numerical model results published for the northern Gulf of Mexico and WFS (Morey et al. 2005; Weisberg et al. 2005) also suggest strong seasonal variations in the flow, with the wind being the major driving force on the inner continental shelf. Long in situ current records in the central and southern WFS have enabled documentation and discussion of the seasonal flows there (Liu and Weisberg 2012), but these measurements are all south of the Big Bend.

Based on the above, there is a need to document and understand in situ estimates of the mean and seasonal flow in the Florida Big Bend. In this section, we provide such estimates from the multiyear in situ measurements now available to us.

a. Depth-averaged along-isobath flow

Our longest records are in 19-m depth at K-Tower, and we focus most of our attention on the results there. As expected from the subinertial results in section 5, and consistent with CTW dynamics, the depth-averaged monthly along-isobath flow at K-Tower is more highly correlated with than with , and depth-averaged monthly along-isobath flow at site S is very similar to that at K-Tower (see Fig. 17).

Fig. 17.

(a) Monthly along-isobath depth-averaged flow at K-Tower (thick solid line) and (thin solid line). The correlation between these time series is r = 0.77 (r95% = 0.42). (b) As in (a), but for replaced by (thin solid line), the local along-isobath wind stress at K-Tower. In this case, the correlation is insignificant (r = 0.13, r95% = 0.43). (c) As in (a), but for replaced by , the monthly depth-averaged along-isobath flow at site S. The correlation is r = 0.86 (r95% = 0.61).

Fig. 17.

(a) Monthly along-isobath depth-averaged flow at K-Tower (thick solid line) and (thin solid line). The correlation between these time series is r = 0.77 (r95% = 0.42). (b) As in (a), but for replaced by (thin solid line), the local along-isobath wind stress at K-Tower. In this case, the correlation is insignificant (r = 0.13, r95% = 0.43). (c) As in (a), but for replaced by , the monthly depth-averaged along-isobath flow at site S. The correlation is r = 0.86 (r95% = 0.61).

Based on the above monthly data, the depth-averaged along-isobath flow at K-Tower, averaged for each of the 12 calendar months, is as shown in Fig. 18. The flow is eastward along the Big Bend coast during June, July, and from October to March, and westward during April, May, August, and September. The maximum eastward flow is 4 cm s−1 in November and maximum westward in May is 3 cm s−1. Consistent with the correlations in Fig. 17a, the stronger eastward flows in January, February, and November correspond to being positive (southward) then, and the stronger westward flows in May and September are consistent with negative (northward) then. Note that these results are based on coincident wind stress and current records for the 40-month period upon which Fig. 18 was constructed.

Fig. 18.

Depth-averaged along-isobath flow as a function of calendar month at K-Tower with standard error for each calendar month. Here and in Fig. 22, the standard error for each calendar month is the standard deviation for each calendar month divided by the square root of the number of monthly data for that particular calendar month. The mean flow is marked by the dashed line and is 0.72 cm s−1. Calculations are based on data from January 2007 to December 2010 under the criterion that a month was only included in the average if more than 99% of the data were available. This resulted in 8 of the 48 months (January 2007, July 2007, and July–December 2010) being excluded. If only 50% of the data were required for each month, two more months, July 2007 and September 2010, could be added to the calendar-month estimates, but the results changed negligibly.

Fig. 18.

Depth-averaged along-isobath flow as a function of calendar month at K-Tower with standard error for each calendar month. Here and in Fig. 22, the standard error for each calendar month is the standard deviation for each calendar month divided by the square root of the number of monthly data for that particular calendar month. The mean flow is marked by the dashed line and is 0.72 cm s−1. Calculations are based on data from January 2007 to December 2010 under the criterion that a month was only included in the average if more than 99% of the data were available. This resulted in 8 of the 48 months (January 2007, July 2007, and July–December 2010) being excluded. If only 50% of the data were required for each month, two more months, July 2007 and September 2010, could be added to the calendar-month estimates, but the results changed negligibly.

b. Vertical structure of the along-isobath monthly flow at K-Tower

Figure 19 illustrates the annual cycle of depth-averaged temperature, salinity, and density at sites A, B, and K-Tower (see Fig. 1). The annual cycle of these quantities at a given depth is similar to the depth-averaged values at these locations. The annual cycle in density at each location is mainly governed by temperature (note the similar annual cycles in Figs. 19a,c), but the large seaward density gradient ρx is mainly due to salinity (see Fig. 20). The seaward salinity gradient is largely because of the influence of the annually and interannually varying Apalachicola River, Florida's largest river [see Morey et al. (2009) for a discussion of the variability and influence of this river on the WFS]. The large seaward density gradient should lead to a vertical shear in the alongshore flow via the thermal wind relationship

 
formula

Integrating (18) vertically from z = −11 to −4 m gives

 
formula

The 4-m depth is the depth nearest the surface where we have reliable velocity data, and the 11-m depth is the deepest available to calculate ρx from hydrographic data at K-Tower and the station next closest to the coast.

Fig. 19.

(a) Depth-averaged temperature as a function of calendar month near K-Tower (thick solid), site B (dashed), and site A (thin solid). (b),(c) As in (a), but for temperature replaced, respectively, by salinity and density.

Fig. 19.

(a) Depth-averaged temperature as a function of calendar month near K-Tower (thick solid), site B (dashed), and site A (thin solid). (b),(c) As in (a), but for temperature replaced, respectively, by salinity and density.

Fig. 20.

Depth-averaged density difference (thick solid, kg m−3) between hydrographic measurements at K-Tower and those at the next closest hydrographic station toward the coast and half way between site B and K-Tower. Corresponding density differences owing to salinity (thin solid) and temperature (dashed) show that the density differences are mainly due to salinity differences. Here, psu−1.

Fig. 20.

Depth-averaged density difference (thick solid, kg m−3) between hydrographic measurements at K-Tower and those at the next closest hydrographic station toward the coast and half way between site B and K-Tower. Corresponding density differences owing to salinity (thin solid) and temperature (dashed) show that the density differences are mainly due to salinity differences. Here, psu−1.

Time series of Δυ from the current meter data at K-Tower and the rhs of (19) from the hydrographic data are compared in Fig. 21. The two time series have a similar amplitude and are correlated at r = 0.67 (r95% = 0.49), suggesting that ρx and the thermal wind balance explains much of the vertical shear. For most of the record Δυ < 0, corresponding to a velocity that becomes increasingly westward with height and consistent with seaward density increase. An exception is the late fall of 2007 and winter of 2008/09 when the density gradient reverses, and, consistently, Δυ > 0, as the velocity is increasingly eastward with height.

Fig. 21.

Low-frequency shear Δυ (thin line) between 4- and 11-m depth [lhs of (19)] and the corresponding Δυ (thick line with dots) estimated using the rhs of (19) and hydrography at K-Tower and the next closest hydrographic station to the coast. The correlation between the spot hydrographic measurements is r = 0.67 (r95% = 0.49).

Fig. 21.

Low-frequency shear Δυ (thin line) between 4- and 11-m depth [lhs of (19)] and the corresponding Δυ (thick line with dots) estimated using the rhs of (19) and hydrography at K-Tower and the next closest hydrographic station to the coast. The correlation between the spot hydrographic measurements is r = 0.67 (r95% = 0.49).

c. Cross-isobath seasonal flow at K-Tower

Figure 22 shows the average calendar-month cross-isobath flow at K-Tower based on approximately 4 years of measurements. In the lower part of the water column the flow is toward the shore but nearer the surface, except for September–November, the flow is of opposite sign, particularly in June and July. The shoreward near-bottom flow is likely influenced by the BBL mechanism discussed in section 7a. By that mechanism, in the usual case when density increases seaward, the zero-mean energetic weatherband along-isobath flow will give rise to a stronger shoreward than seaward BBL flow, that is, a rectified near-bottom flow toward the coast.

Fig. 22.

At K-Tower, the calendar month–average across-isobath flow at (a) 4-m beneath the surface, (b) the depth-averaged across-isobath flow, and (c) the cross-isobath flow 3-m above the bottom. Negative flow corresponds to shoreward flow. The dashed lines denote annual averages and are 0.74 cm s−1 in (a), −0.26 cm s−1 in (b), and −1.1 cm s−1 in (c). The results are based on the 4-yr calendar record using the 99% criterion as in Fig. 18; error bars correspond to standard error.

Fig. 22.

At K-Tower, the calendar month–average across-isobath flow at (a) 4-m beneath the surface, (b) the depth-averaged across-isobath flow, and (c) the cross-isobath flow 3-m above the bottom. Negative flow corresponds to shoreward flow. The dashed lines denote annual averages and are 0.74 cm s−1 in (a), −0.26 cm s−1 in (b), and −1.1 cm s−1 in (c). The results are based on the 4-yr calendar record using the 99% criterion as in Fig. 18; error bars correspond to standard error.

9. Concluding remarks

The preceding analysis of the long time series of currents and hydrography in the Big Bend region has led to some key results summarized below.

  • The subinertial flow in the Big Bend region in 19 and 10 m of water is largely remotely driven by wind stress parallel to the axis of the Florida Peninsula to the south in accordance with coastally trapped wave dynamics and previous work. The Florida Keys “cut off” the WFS in the south and essentially exert a “brake” on the generation of the along-isobath flow, making it smaller compared to that which would have been generated by the same wind on a shelf without the Keys. The subinertial flow in 5-m water depth, especially in winter, is locally wind driven.

  • The huge Big Bend cross-shelf density gradients, due largely to the freshwater flux near the coast, have a profound influence on the cross-isobath flow. By standard bottom boundary layer dynamics, the quasigeostrophic along-isobath flow will induce bottom boundary layer transport toward and away from the coast depending on the along-isobath flow direction. However, because density usually increases strongly offshore in the Big Bend region, seaward bottom boundary layer flows result in less dense water being forced under more dense water. Gravitational instability and mixing disrupt the bottom boundary layer flow and severely reduce it. By contrast, shoreward bottom boundary layer flow results in denser water underlying less dense water, and there is no gravitational instability and reduction of the cross-isobath flow by the mixing mechanism.

  • When there is a winter drought, as often occurs during La Niña (see, e.g., Morey et al. 2009), the freshwater flow is decreased, the seaward salinity gradient decreases, and the cooler winter temperature in the shallower water nearer the coast can reverse the density gradient. In this rarer case it is the shoreward bottom boundary layer flow that moves lighter water under heavier water and, so, causes gravitational instability and mixing and decreased cross-shore flow.

  • Analysis showed that, if numerical models are to model the flow accurately, they must resolve the bottom topography on scales less than 5 km. Also, they must be able to model correctly the mixing cross-isobath mechanism summarized under (ii) and (iii) above.

  • The results under (ii) imply that the subinertial across-isobath flow is rectified. Specifically, if the subinertial along-isobath flow has a zero mean, the frictionally induced cross-isobath bottom boundary layer flows will not have a zero mean—the flow will be rectified so that there is a net onshore bottom boundary layer transport, about 10 m thick, toward the coast. This may at least partly explain the mean shoreward bottom boundary transport for all calendar months of the year.

  • Like the subinertial flow, seasonal along-isobath depth-averaged flow is remotely forced by . It varies from a maximum westward flow of 3 cm s−1 in May to a maximum eastward flow of 4 cm s−1 in November, with an overall mean of about 1 cm s−1 eastward. Because of the cross-shelf density gradient, the monthly along-isobath flow is vertically sheared in accordance with the thermal wind relationship.

Acknowledgments

We gratefully acknowledge grant support of the Florida Institute of Oceanography (Grant 4710-1101-05-A), the Florida Fish and Wildlife Research Institute (DO364787, DO591065 and DO1191327), the Northern Gulf Institute (Grant 000013122), BP/the Gulf of Mexico Research Initiative to the Deep-C Consortium, and the National Science Foundation (Grants OCE-0850749 and OCE-1155257). We thank Stephanie Fahrny White and Peter Lazarevich of the FSU Marine Field Group, and the FSU Marine Lab, especially Captain Rosanne Weglinski, for dedicated collection of the data.

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