Mixing of a dye tracer in the Delaware plume: Comparison of observations and simulations

Transcription

1 JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 112,, doi: /2006jc003928, 2007 Mixing of a dye tracer in the Delaware plume: Comparison of observations and simulations C. E. Tilburg, 1,2 R. W. Houghton, 3 and R. W. Garvine 4 Received 7 September 2006; revised 28 February 2007; accepted 31 July 2007; published 8 December [1] In April 2003 we injected Rhodamine-WT fluorescent dye into the halocline at the base of the Delaware River plume during an upwelling event. The dye immediately bifurcated: One third of the dye moved offshore with a portion of the plume, while the other 2/3 remained within the halocline, near the coastline. This behavior has not been previously observed, and it presents a strong challenge to contemporary coastal ocean models. Here we employ a numerical model of Delaware Bay and the adjacent coastal region that incorporates the Mellor-Yamada Level 2.5 turbulence closure scheme to simulate the observed dye injection event. Comparison between the simulation and observations reveals that the model is able to successfully reproduce the flow field, simulating the separation and subsequent advection of the dye. Consequently, the simulation is used to examine the relative effects of wind- and buoyancy-driven transport on mixing and advection of the dye. Comparison of simulated and observed plumes reveals that the model accurately reproduces the observed mixing and accompanying vertical salt flux within the offshore plume. Examination of the simulation reveals a unique combination of wind- and buoyancy-driven flow that results in the dye remaining in the halocline of the onshore plume despite significant vertical mixing due to winds. The strong stratification within the inshore plume causes the closure scheme to shut off the vertical diffusivities, leaving the circulation model with arbitrarily chosen constant background values. Varying these values reveals only a weak dependence of the salt flux within the highly stratified regions due to the highly localized nature of the salt flux. Citation: Tilburg, C. E., R. W. Houghton, and R. W. Garvine (2007), Mixing of a dye tracer in the Delaware plume: Comparison of observations and simulations, J. Geophys. Res., 112,, doi: /2006jc Introduction [2] Discovering the primary processes that control acrossmargin transport of biologically, geologically, and chemically important materials has first rank priority in ocean science. A major component of this transport is produced by freshwater inflow to the continental margin from rivers and estuaries. The NSF Coastal Ocean Processes (COOP) buoyancy workshop held in October 1998 emphasized the importance of freshwater inflow among shelf circulation processes. The workshop report [Henrichs et al., 2000] stated the importance of freshwater inflow and noted that.. coastal ocean regions with large freshwater inflows are major gateways for the transfer of materials from continents to oceans. In part because of nutrients supplied 1 Department of Marine Sciences, University of Georgia, Athens, Georgia, USA. 2 Now at Department of Chemistry and Physics, Marine Science Center, Biddeford, Maine, USA. 3 Lamont-Doherty Earth Observatory of Columbia University, Palisades, New York, USA. 4 College of Marine and Earth Studies, University of Delaware, Newark, Delaware, USA. Copyright 2007 by the American Geophysical Union /07/2006JC with the fresh water, these areas tend to be highly productive and to support major fisheries. [3] Of first importance among the physical processes affecting transport by freshwater inflow are the mixing processes that blend upland fresh water into the coastal ocean. What are the major agents that promote this mixing? Four commonly postulated agents are (1) tidal mixing, especially near the estuary; (2) direct stirring by the wind acting on the water surface; (3) instability of the buoyancy driven coastal current that forms downshelf (i.e., in the direction of Kelvin wave propagation) from the freshwater discharge; and (4) the straining action of wind driven coastal Ekman circulation. This straining is a consequence of differential across-shelf motion with resulting fluid deformation. [4] The evidence to date from model studies and field observations is that coastal Ekman circulation, especially upwelling circulation, is the most effective mixing agent. Flow instability and resulting eddy generation and enhanced mixing are processes with great potential for mixing in buoyancy driven coastal plumes, but the limited observations available at present show this mechanism to be rare. Several field studies have examined tidal mixing. Blanton and Atkinson [1983] studied the transport and fate of fresh water on the shelf of the South Atlantic Bight. They concluded that tidal energy was too weak to provide much 1of15

2 mixing, except during times of extremely low runoff. The chief mixing agent, instead, was wind stress acting to generate coastal upwelling circulation. Simpson et al. [1993] studied the Rhine inflow to the North Sea. They found that tidal mixing, especially during spring tides, and mechanical mixing by wind stress controlled the stratification. Sanders and Garvine [2001] found evidence of intermittent tidal mixing near the source of the Delaware Coastal Current. [5] The impact of coastal Ekman circulation on plume mixing with shelf water has been the subject of both model and field studies. Fong and Geyer [2001] used a numerical model to study the action of upwelling favorable wind stress on an idealized buoyant coastal plume. They found that Ekman circulation led to the offshore advection of the horizontal density gradient, which was then balanced by vertical mixing. Hallock and Marmorino [2002] found from observations of the Chesapeake plume that upwelling winds as short as one half-day s duration sufficed to generate an upwelling response in the plume. Sanders and Garvine [2001] showed evidence from Lagrangian measurements of the Delaware Coastal Current that upwelling winds induced rapid mixing between upland fresh water and ambient shelf water, while downwelling winds produced much weaker mixing. [6] The treatment of these mixing processes in numerical modeling in stratified regions such as buoyant plumes is undergoing substantive review. Several researchers have noted [e.g., Kantha and Clayson, 1994; Garvine, 1999] that contemporary turbulent closure models used in circulation models, including the k-epsilon (ke) and the Mellor and Yamada [1982] submodels, abruptly switch off the turbulent eddy coefficients when even moderate levels of stratification appear. These submodels return zero values for vertical eddy viscosity and diffusivity, leaving the circulation model with arbitrarily chosen constant background values. For the Richardson number values found in most buoyant plumes, the coefficients for the great bulk of the plume body are often set by default to these background values. [7] In nature, complex physical processes likely set the level of vertical viscosity and diffusivity for conditions of bulk Richardson number above critical. In a study of upwelling off the Oregon coast, Avicola et al. [2006] found that the internal tide and near inertial motion contributed to the vertical shear. These combined with the low-frequency shear associated with thermal wind balance in the upwelling jet to lower the effective local Richardson number values below critical, greatly increasing the local vertical salt flux. Similar mechanisms may be at work in a stratified plume such as the Delaware. Observations that yield close estimates of vertical eddy viscosity and vertical diffusivity in a buoyant coastal plume would be invaluable for closure model improvement. [8] This study builds on field observations performed in April 2003 using dye injected into the halocline of the Delaware River plume during a strong upwelling event [Houghton et al., 2004] that examined the effect of Ekman straining on the across-shelf transport and vertical mixing with the buoyant plume. In this paper, we continue the analysis of the effects of upwelling winds on a buoyant plume using a combination of those observations and a numerical model of Delaware Bay and the adjacent coastal region [Whitney and Garvine, 2005] that incorporates the Mellor-Yamada closure scheme. Here, we examine the relative effects of buoyancy- and wind-driven transport on the buoyant plume in the coastal environment as well as compare the parameterization of vertical mixing in a numerical simulation using one of the most commonly used turbulence closure schemes in coastal oceanography. 2. Methods 2.1. Observations [9] In a study to examine mixing in a buoyant plume during an upwelling wind event, a shipboard survey was conducted within the coastal region adjacent to Delaware Bay (Figure 1) over a 3 d period in the spring of We completed an initial survey of the region between 1630 UTC, 14 April 2003 (hereinafter referred to as yearday or yd ), and 0500 UTC, 15 April 2003 (yd ). At yd , we injected 48 kg of Rhodamine-WT fluorescent dye at 5 6 m depth into the halocline at the base of the Delaware River plume southeast of Cape Henlopen, Delaware (Figure 2a). The dye quickly evolved into a 600 m long streak oriented northeast to southwest 8 km inshore of the seaward edge of the plume. Surveys of the dispersing dye patch commenced immediately. Dye concentrations were measured using a Chelsea Ltd. MKIII Aquatracka fluorometer fitted to a Sea Bird SBE-911 CTD, all attached to an undulating towed vehicle (Scanfish). A full description of the initial injection is provided by Houghton et al. [2004]. An array of five moorings (Figure 1) complemented the ship-borne measurements. Each mooring consisted of a bottom mounted RDI acoustic Doppler current profiler (ADCP), two InterOcean S4 electromagnetic current meters, and chains of SeaBird SBE-37SM conductivity and temperature sensors. All instruments returned usable data except for the surface S4 current meter at mooring A Numerical Model [10] We compared the field observations of dye concentration, salinity, and velocity fields to output from a numerical circulation model that realistically simulated the physical dynamics within the study area. The circulation model used in this study was ECOM3d, a primitive equation finite-difference model in sigma (terrain following) coordinates based on the model developed by Blumberg and Mellor [1987]. The model was modified to encompass Delaware Bay, a portion of the Delaware River, and the adjoining coastal region. ECOM3d has been used extensively to study transport on coastal shelves [e.g., Kourafalou et al., 1996; Whitney and Garvine, 2005, 2006; Tilburg, 2003]. The model used here is an extension of that described by Whitney and Garvine [2006], who validated the model with a series of observations of currents and hydrographic surveys obtained during the spring of Consequently, the model is only briefly described here and the interested reader is referred to Whitney and Garvine [2006] for a more comprehensive description. [11] The coastline and model bathymetry are based on data provided by the National Oceanic and Atmospheric Administration (NOAA) National Geophysical Data Center. 2of15

3 Figure 1. Location of study site showing location of moorings. Dark gray box shows region depicted in Figure 2. Light gray box shows region depicted in Figure 4. Inset shows location of site (arrow) along the east coast of the United States. The model domain extends 110 km upshelf of Delaware Bay past Atlantic City, New Jersey, 230 km downshelf to the Chesapeake Bay mouth, and approximately 120 km offshore. The offshore boundary is irregular and located along the 100 m isobath. Its free surface is fixed to the tidal height by specifying the amplitude and phase of the semidiurnal M2 tidal height constituent derived from an inverse tidal model incorporating TOPEX/Poseidon altimetry data [Egbert et al., 1994]. The two across-shelf boundaries use a combination of clamped and radiation conditions that are specifically developed to realistically treat tidal, wind, and buoyancy forcing [Whitney, 2003]. Flow at the bottom boundary is governed by a quadratic drag law. Vertical mixing is provided by the Mellor-Yamada level 2.5 turbulence closure scheme, while horizontal eddy viscosities and diffusivities are treated by the Smagorinsky scheme [Smagorinsky, 1963]. Since ECOM3d is a sigma level model, the vertical resolution is proportional to water depth. The simulations within this study contain 15 sigma levels whose spacing is much closer near the surface and the bottom boundaries to better resolve the surface and bottom Ekman layers. The vertical grid size ranges from a minimum of 0.15 m within Delaware Bay to a maximum of 5 m near the offshore boundary. The model grid contains grid cells covering the 340 km 240 km domain. The horizontal grid size for the simulation varies from 0.75 km within Delaware Bay to 3 km on the shelf. However near the boundaries, grid sizes increase to 8 km. The model uses a split time step of 9.2 s for the barotropic mode and 92 s for the baroclinic mode. [12] The model was forced by winds obtained from hourly observations from the NOAA environmental buoy (EB44009) located off the mouth of Delaware Bay. Comparison of wind speed at coastal stations (e.g., Atlantic City Airport) with EB44009 reveals a decrease near the coast [Whitney, 2003]. To account for across-shelf gradients in wind speed, pthe ffiffi winds within the bay and near the mouth were set to 1/ 2 of the measured wind speed (or 1/2 wind stress) at EB This correction is consistent with earlier studies [e.g., Willmott et al., 1985] of wind stress on the continental shelf and at coastal stations. On the shelf, the winds were set equal to the wind speed measured at the buoy. Freshwater discharge was specified as the daily mean river flow at Trenton, NJ multiplied by 1.6 to reflect other rivers in the lower basin and lagged at 5 d. [13] The model dye injection was simulated by the introduction of neutrally buoyant dye into five sigma levels spanning the halocline at a time that corresponded to the observed injection event. The model was then run for a total of 4 d as the dye dispersed through the model domain. To examine the effects of different background vertical viscosities on the overall behavior of the plume, three simulations were performed with different background viscosities: m 2 s 1 (base simulation used in the 3of15

4 Figure 2. Spatial map of initial salinity conditions for (a) surface layer gathered from observations from yearday (yd) , (b) surface layer gathered from simulations sampled at same time as observations, (c) snapshot of surface layer at yd , (d) 10 m depth layer gathered from observations from yd , (e) 10 m depth layer gathered from simulations sampled at same time as observations, and (f) snapshot of 10 m depth layer at yd Black circle indicates location of injection. majority of the paper), m 2 s 1 (referred to as S4), and m 2 s 1 (S7). 3. Results 3.1. Observations [14] Examination of the initial survey of the region indicates that the river plume had been confined to the coast (Figure 2) by strong, persistent northerly (downwelling) winds (Figure 3) the previous week. However, the dye injection was immediately preceded by the onset of a strong upwelling-favorable wind event (southerly winds >5 m s 1 ) that lasted throughout the time of the observations. The rapid switch to strong, persistent upwelling winds provided an unusually clean initial condition and physical setting for the experiment. [15] The dye was injected at yd into the halocline over a salinity range of 25.2 to At injection, the halocline spanned approximately 4 to 6 m depth with a salinity interval of 27.5 to 31. The strong vertical shear at this depth suggests that the injection was near the base of the wind-forced surface Ekman layer. This vertical shear in Figure 3. Time series of wind vectors during the cruise and for 3 d immediately preceding and following the cruise. Period of the cruise is designated by shaded region. Dye injection event is designated by the heavy vertical line at day of15

5 Figure 4. Map of study region showing the time evolution of the surface salinity (psu) (contour lines) and integrated dye concentrations (parts per by weight m) (filled contours) for the observed (left) and simulated (right) dye injections. Red lines indicate the transects shown in Figure 5. Time indicated on the observed frames (left) represents the time from start to finish of each survey. Contour interval of salinity is 0.5 psu. Note that the observations do not include the upper 2 m of the water column, since the Scanfish was not able to sample this region. Since the majority of the dye resides in the upper 2 m in the offshore plume, the observed integrated concentrations are significantly lower than the simulated values. the across-shelf flow caused the dye to quickly bifurcate. Examination of the observed integrated dye concentrations (Figure 4, left) reveals that approximately 2/3 of the dye remained near the coastline (hereinafter referred to as patch A), while 1/3 of the dye quickly moved offshore (hereinafter referred to as patch B). Near the end of the experiment (yd ), both patches were located within relatively strong horizontal salinity gradients, indicating that they were at the downshelf (patch A) and offshore (patch B) edges of the plumes. [16] Vertical sections of the dye patches (Figure 5) show that the dye had separated both vertically and horizontally by yd Patch A initially remained below the surface Ekman layer and did not exhibit a strong advective response to the wind forcing; however, patch B was entrained into the surface Ekman layer and quickly moved offshore. An across-shelf transect near the end of the experiment (yd ) reveals strong stratification inshore and offshore, separated by shoaling isohalines, suggesting that two separate plumes were present in the region: the portion of the initial plume that moved offshore during the upwelling event (affecting patch B) and the portion of the plume that remained inshore (affecting patch A). [17] To determine mixing rates and vertical velocities of the dye patches, we examined the time dependence of the depth and salinity of the centers of the dye patches (Figure 6). The observed depth and salinity (red and blue circles in Figure 6) were recorded at the location of the maximum dye concentration measured on each individual section. The minimum salinity measured at the ship s 1 m water intake on each individual section was assumed to be the observed plume salinity (diamonds in Figure 6a). When the dye separated into two distinct patches, a number of surveys were performed on each patch until the distance between the two patches became too great (at approximately yd 105.8), at which time the observations concentrated on the offshore patch B, returning to patch A only after yd [Houghton et al., 2004]. [18] Immediately after injection (yd ) the dye began to separate and the dye patch B (red circles in Figure 6) began to freshen and shoal. At yd , patch B was in the surface mixed layer and the dye and Figure 5. Sections through dye patch showing the time evolution of the salinity (psu) (white contour lines) and dye concentration (parts per by weight) (filled contours) for the observed (left) and simulated (right) dye injections. Gray represents concentration values <1 part per Contour interval of salinity is 0.5 psu. Note that the observations do not include the upper 2 m of the water column, since the Scanfish was not able to sample this region. 5of15

6 Figure 5 6of15

7 Figure 6. Time variation of the (a) salinity and (b) depth (meters) at the maximum dye concentration within the observed (red and blue circles) and simulated (red and blue lines) dye patches A and B. Salinity of the observed (diamonds) and simulated (black line) plume are also shown in Figure 6a. plume salinity were approximately equal, indicating that the dye patch was at the center of the plume. After yd , the salinity of both the dye patch and the surrounding buoyant plume began to increase as the plume moved offshore. The salting rate of the dye patch was greater than the plume s salting rate, indicating that the patch was moving to the seaward side of the plume. [19] The observed dye patch A (blue circles in Figure 6) remained below the Ekman depth and slowly increased in depth and salinity. Although the ship had moved away from this patch by yd 105.8, it returned after yd and found that a significant portion of patch A had remained in the halocline (blue circles at yd in Figure 6). Examination of an alongshelf section at yd (Figure 7, left) reveals that the dye in patch A resided in the halocline at the latitude (38.6 N) of the across-shelf section in Figure 5. The halocline shoaled downshelf. Although the upper 2 m were not sampled by the Scanfish, the large dye concentration directly below 2 m suggests that a significant portion of the dye resided within the halocline and at the surface near the downshelf edge of a buoyant plume propagating downshelf. [20] Examination of the observed water column salinity at moorings DC, A1, DB, and DA (Figure 8, left) indicates Figure 7. Alongshelf section showing salinity (psu) (white contour lines) and dye concentration (parts per by weight) (filled contours) for the observed (left) and simulated (right) dye injections. Gray represents concentration values <1 part per Contour interval of salinity is 0.5 psu. Note that the observations do not include the upper 2 m of the water column, since the Scanfish was not able to sample this region. Inset shows location of section. 7of15

8 Figure 8 8of15

9 that, before the onset of upwelling, surface salinity and stratification throughout the region were governed by the buoyant plume as it moved into and out of the mooring array. At the closest mooring to the mouth of the bay (mooring DC), the surface salinity varied at tidal frequency as freshwater was expelled from Delaware Bay during ebb tides and coastal water entered during flood tides but did not show any significant response to the upwelling event. The mooring closest to the coast (A1) was characterized by the lowest salinity of any mooring before yd , consistent with a geostrophically adjusted buoyant plume. After the onset of upwelling and the resultant offshore Ekman transport, the surface salinity at A1 increased as the plume moved offshore. Afterward, the salinity and stratification varied at tidal frequency, indicating that the mooring was still affected by the plume. By yd 106.0, the surface salinity had increased from 26 to 30. At mooring DB, the surface salinity dramatically decreased after yd and remained low for the duration of the observations, indicating that the plume remained near this mooring. Again, the salinity and stratification varied at tidal frequency, indicating that the plume was advected back and forth over the mooring. At mooring DA, which was both the farthest from the mouth and farthest from the shore, salinity began to decrease by yd , reaching a minimum at yd 106, but increased after that with little or no tidal variations, indicating that the plume had moved offshore past the mooring. [21] Velocities obtained from surface mounted S4 current meters (gray arrows in Figure 9) show strong tidal frequency oscillations at all moorings. The strongest velocities were at mooring DC where the tidal flow was constricted by the mouth of the bay. Again, the velocities here showed little effects due to winds. However, at the moorings further from the mouth (A1, DB, and DA), the upwelling winds resulted in a decrease in downshelf velocities during ebb tide and an increase in upshelf velocities during flood tide. At all moorings downshelf tidal flow coincided with increased stratification at each mooring, indicating that the alongshelf advection of the buoyant plumes offshore (moorings DB and DA) and inshore (moorings DC and A1) were responsible for variations in salinity and stratification. [22] While the movement and mixing of the offshore plume is consistent with previous studies [e.g., Fong and Geyer, 2001; Lentz, 2004], the movement of the onshore plume as determined by the dye is puzzling. Why was the observed onshore dye confined to the halocline? Why was an onshore plume present at all during strong upwelling winds? The limited observations suggest that the onshore plume was due to a combination of wind- and buoyancydriven flow; however, the observations do not provide sufficient detail to determine the underlying physical mechanisms that govern the evolution of the plume. In the next section, we compare the numerical simulation to observations of the flow, salinity, and dye concentration fields. The agreement of the simulation and observations suggests that the physical mechanisms within the simulation are consistent with those in the observed Delaware River plume and allow us to examine the evolution of the onshore plume in greater detail Numerical Simulations [23] While observations tend to suffer from incomplete temporal and spatial resolution that can complicate interpretation, numerical simulations are able to provide complete flow and density fields that are in dynamical balance. However, simulations are based on a number of assumptions that may or may not be justified and must be validated with available observations before dynamical interpretations can be made. To remove errors in the comparison between observations and the simulations due solely to water movement during the actual survey and subsequent contouring of this incomplete field, the simulated salinity field was sampled at the same times and locations as the observed salinity field (Figures 2a and 2d) and a contour plot was created from these sampled data (Figures 2b and 2e). Comparison of the initial simulated and observed conditions (Figure 2) reveals qualitative agreement between the observations and the simulation. Contour plots from both observations and the simulation show a buoyancy-driven current that extends to a depth of 10 m (Figures 2b and 2e) and extends downshelf of the survey, although the simulated plume was characterized by slightly fresher surface water and more saline water at depth. A comparison of a snapshot of the simulated salinity field at yd (Figures 2c and 2f) with the contour plot obtained from the temporally varying sampling (Figures 2b and 2e) reveals significant differences, indicating that the region is characterized by strong temporal and spatial variations due to tides, buoyancy, and winds and the nonsynoptic nature of the survey can introduce errors [Matthews, 1997]. [24] Comparison of the evolution of the dye patches (Figures 4 and 5) reveals qualitative agreement between the observations (Figures 4 and 5, left) and the simulation (Figures 4 and 5, right) in the timing of separation and the subsequent advection and vertical mixing of the patches. The simulated patch B was entrained into the surface layer and moved offshore with the Ekman transport in a similar manner to the observations. By yd , both the simulated and observed patch B were oriented across-shelf within a salinity gradient, indicating that the patches were moving through the seaward edge of the buoyant plume. [25] Both the observed and simulated patch A remained below the halocline and moved slowly onshore. Comparison of the integrated dye concentrations of patch A reveals that both simulated and observed patches were near the downshelf and offshore edge of the remaining inshore plume. However, there were some differences between the simulation and observations in the vertical evolution of patch A. By the end of the field study (Figure 5, bottom), the portion of the simulated plume associated with patch A was significantly less stratified than observed and a portion of the simulated dye within patch A had mixed to the bottom of the water column in contrast to the observed patch, where the dye remained trapped in the halocline. Figure 8. Time variation of observed (left) and simulated (right) salinities at moorings DC, A1, DB, and DA. Dye injection event is designated by the white vertical line at day of15

10 Figure 9 10 of 15

11 [26] To better examine the temporal evolution of the simulated dye patches, the depth and salinity of the simulated tracer (red and blue lines in Figure 6) were determined at the values of the maximum dye concentration in the entire model domain at each time step before separation and within each patch after separation. The minimum salinity within the simulated offshore plume at the surface at each time step was assumed to be the simulated plume salinity (black line in Figure 6a). Examination of Figure 6 indicates that the simulated tracer separated shortly after injection in agreement with observations. Dye patch B (red line in Figure 6) shoaled and freshened at similar rates to the observed patch B. By yd 105.4, the maximum concentrations in the patch were found at the surface. (As should be expected, the simulated surface salinities corresponding to these concentrations were slightly less than the observed salinities, since the Scanfish was not able to sample above 2 m depth.) By yd 106.0, the salinity of the simulated patch B began to increase faster than the plume, as it moved through the plume. The simulated patch A (blue line in Figure 6) moved slowly onshore while increasing in salinity in agreement with observations. The majority of the simulated and observed patches were confined to the halocline (Figure 5). However, the depth of the maximum concentration of simulated patch A (blue line in Figure 6b) was slightly less than observed (blue circles in Figure 6b). [27] Examination of the alongshelf transect of patch A reveals qualitative agreement between observations (Figure 7, left) and the simulation (Figure 7, right). The majority of the simulated patch was contained within the halocline but a significant amount had shoaled to the surface. Both observations (Figure 7, left) and simulation (Figure 7, right) show some tracer below the halocline, although the simulation was characterized by slightly greater downward flux resulting in more tracer below the halocline. [28] Comparison of the simulated and observed salinities at moorings DC, A1, DB, and DA (Figure 8) also reveals that the simulation reproduces the observed movement of the plume. The salinity at mooring A1 increased after yd 106.0, indicating that the center of the simulated plume had moved past the mooring; although there was still periodic stratification due to tidal advection of the plume. Mooring DB experienced a decrease in salinity after yd and periodic variations in stratification afterward. The simulated variations in stratification at the two moorings were less than observed, which is consistent with the weaker simulated surface velocities at each mooring (black arrows in Figure 9). Near the mouth of Delaware Bay (mooring DC) and offshore (mooring DA), the simulated stratification agreed quite well with observations, consistent with better agreement in simulated and observed velocities at these moorings. 4. Discussion [29] While Houghton et al. [2004] have described the evolution of the offshore moving plume, the agreement of the observations and the simulation encourages detailed examination of the mixing of the whole field of the dye using the simulation. Here we examine the evolution of the inshore patch using only the simulation. Examination of the simulated surface salinity (Figure 4, right) shows that, at yd 105.6, the region was dominated by one large plume, flanked by more saline water on- and offshore of the plume. However, by yd a secondary salinity gradient was evident at approximately 74.9 W. By yd 106.7, the inshore surface salinity gradient was quite strong and the two patches were separated by more saline water, indicating two separate plumes. Examination of the across-shelf sections (Figure 5, right) confirms the presence of two separate plumes. [30] What accounts for the presence of the inshore plume and confinement of the dye there within the halocline? Austin and Lentz [2002] used a two-dimensional model to examine coastal upwelling and found that a stratified coastal shelf subjected to upwelling winds developed a region of less dense, vertically homogeneous water near the coast because of the interaction of the surface and bottom layers. However, for our case the strong halocline present within the inshore plume precludes this mechanism. Instead, we find that the formation of this inshore plume in our simulation was due to the combination of buoyant flow originating in Delaware Bay and across-shelf flow due to upwelling winds. [31] The inshore plume (patch A) was characterized by strong vertical shear that resulted in downshelf movement at the surface but slight upshelf movement at depth. This vertical shear had a profound influence on the dye. Using the 27 psu salinity contour as a proxy for the downshelf edge of the buoyant plume, we see the simulated buoyant plume moved downshelf from yd to yd (Figure 10). At yd , the maximum concentration of patch A had moved onshore, consistent with across-shelf upwelling circulation, and resided within the halocline (Figure 10, top). However, by yd the wind-induced vertical mixing resulted in the shoaling of the dye (Figure 10, middle). As the buoyant plume moved downshelf through the region, the dye continued to shoal but the dye at the surface was transported downshelf and separated from the majority of patch A which remained below the halocline where the downshelf velocities within the plume were weak (Figure 10, bottom). The combination of the strong halocline (which inhibited vertical mixing) and vertical shear (which transported any surface dye downshelf) resulted in the majority of patch A remaining within the halocline bounded by lower concentrations below and above (Figure 7). [32] The primary objective of this study is the examination of mixing and circulation in a Lagrangian reference frame under the action of a strong upwelling favorable wind. The combination of the observations and the numerical model provides an ideal comparison of vertical mixing within the numerical model. [33] The evolution of the offshore plume was consistent with idealized numerical and theoretical studies [e.g., Fong Figure 9. Time series of observed (gray) and simulated (black) surface velocity (m s 1 ) vectors at moorings DC, A1, DB, and DA. Dye injection event is designated by the heavy vertical line at day of 15

12 Figure 10. Alongshelf sections through dye patch showing the time evolution of the simulated salinity (psu) (white contour lines) and normalized dye concentration (filled contours) for dye patch at edge of buoyant plume. Gray represents concentration values <0.1. Black line represents the 27 isohaline. Contour interval of salinity is 0.5. Inset shows location of section within study region. and Geyer, 2001; Lentz, 2004] of upwelling wind-driven circulation. Fong and Geyer [2001] found that a scaling for the thickness, h c, of a buoyant plume acted upon by upwelling winds is t 4Ri w 6 cr rf h c 4 g Dr r 7 5 ð1þ where f is the Coriolis parameter, r is density, Ri cr is some critical Richardson number, g is the gravitational acceleration, Dr is the plume density anomaly, and t w is the surface stress. Examination of the numerical simulation output at yd 106.0, reveals that the surface stress 0.1 N in the vicinity of the plume. Using f s 1, Dr 3.9 kg m 3, and r 1024 kg m 3, equation (1) yields a plume thickness of 4.0 m. Although this estimate neglects entrainment [Lentz, 2004], it is consistent with the simulated thickness of the offshore plume which ranges from 3 to 4.5 m on yd The temporal increase in simulated thickness (Figure 5) is also consistent with theoretical studies of the effect of entrainment on the evolution of the plume [Lentz, 2004]. 12 of 15

13 Figure 11. (a) Gradient Richardson number, (b) vertical diffusivity (m 2 s 1 ), and (c) salt flux (m s 1 ) taken along the simulated section at yearday Salinity (white contour lines) is superimposed on each figure. Contour interval of salinity is 0.5. Numbered boxes in Figure 11a indicate the regions in which average values are shown in Table 1. [34] Direct comparison of the simulation with observations reveals that the model was able to reproduce the observed mixing in the offshore plume. Houghton et al. [2004] estimated that the average salt flux through the observed patch B was approximately (± )ms 1 and the average effective vertical diffusivity, K z, was (± )m 2 s 1 in a plume whose bulk Richardson number, Ri, was 0.6 ± 0.2. The observed Ri was greater than the critical Richardson number Ri cr (0.25). Examination of the simulated Ri along the across-shelf section at yd 106 reveals that Ri > 0.25 (dark red in Figure 11a) throughout most of the plume, in 13 of 15

14 Table 1. Mean Values of Mixing Parameters of Base Simulation a Parameter Box 1 Box 2 Box 3 Box 4 Ri 0.88 (1.2) 0.31 (0.41) 0.23 (0.41) 0.14 (0.16) K z,m 2 s ( ) ( ) ( ) ( ) Salt flux, m s ( ) ( ) ( ) ( ) a Standard deviations are in parentheses. Ri is the Richardson number. K z is the average effective vertical diffusivity. agreement with these observations. These large values of Ri resulted in the shut-off of the turbulence closure scheme and a simulated K z of m 2 s 1 (dark blue in Figure 11b), which is simply the user chosen background vertical diffusivity. [35] The combination of K z and the vertical salinity gradient can be used to calculate the vertical salt flux (Figure 11c) whose peak value of approximately ms 1 occurred at the base of the seaward edge of the plume. While the plume was predominantly characterized by Ri > Ri cr, there were still significant spatial variations. Near the surface, values of Ri were an order of magnitude less than Ri cr (Figure 11a). Beneath the plume, Ri was again considerably less than the smallest value in the plume. The variations in Ri resulted in large changes in both K z and vertical salt flux. [36] Examination of mean values of Ri, K z, and salt flux (Table 1) for four different sections of the plume (numbered boxes in Figure 11a) reveals that the inshore portion of the plume (boxes 1 and 2) had higher Ri than the offshore portion of the plume (boxes 3 and 4), which resulted in lower values of K z. Also the higher stratification present within the plume (boxes 1, 2, and 3) resulted in higher Ri and lower K z than the region directly below the plume (box 4). The entire plume was characterized by significant spatial variations in all properties. The standard deviations of salt flux, K z, and Ri were larger than the mean values for each box. Salt flux was greatest at the base of the plume near the seaward edge of the plume (box 3) and onshore (box 2), in agreement with previous numerical [Fong and Geyer, 2001] and theoretical [Lentz, 2004] studies showing that the majority of the salt flux occurs near the seaward edge of a plume during upwelling winds. The vertically averaged estimates of Ri, K z, and salt flux from observations [Houghton et al., 2004] were made over the depth of the offshore-moving plume. Direct comparison of these observed values with the mean simulated values within box 3 reveal that the simulated average Ri was less than observed (0.23 versus 0.62) and less than Ri cr, which resulted in a significantly higher K z ( m 2 s 1 versus m 2 s 1 ). However the observed ( ms 1 ) and simulated salt fluxes ( ms 1 ) are within 1 standard deviation of each other. [37] The pockets of low Ri in the simulated offshore plume (box 3) resulted in an average value that was less than Ri cr, avoiding switching off of the turbulence closure scheme. Meanwhile the mean Ri in the inshore portion of the plume (boxes 1 and 2) were greater than Ri cr, resulting in vertical diffusivities that were close to the background values chosen by the user. Consequently, to determine the sensitivity of the simulation to the choice of background diffusivity we performed simulations using two other background diffusivities: m 2 s 1 (S4) and m 2 s 1 (S7), the latter only slightly more than the molecular value. Examination of the mean K z (Base = m 2 s 1 ;S4= m 2 s 1 ;S7= m 2 s 1 ) and salt flux (Base = ms 1 ;S4= m s 1 ;S7= ms 1 ) within the offshore plume (box 3) reveals little variation from the base simulation, which is expected since mean values of Ri of all three simulations (0.23, 0.14, 0.19 for base, S4, and S7, respectively) were similar and <0.25. However, within the inshore plume mean Ri of all three simulations >0.25, indicating that the circulation model relied on the user chosen background diffusivity for vertical mixing. The inshore plume (box 1) was characterized by median K z values that were near to the background for all simulations ( , , and m 2 s 1 for base, S4, and S7, respectively). However, the pockets of higher K z resulted in mean values that were significantly higher than background for the base simulation ( m 2 s 1 ) and S7 ( m 2 s 1 ) and slightly higher for S4 ( m 2 s 1 ). This variation in the mean values of K z resulted in some variation in salt flux ( , , and ms 1 for base, S4, and S7, respectively) that inversely correlated with user-chosen background diffusivity. However, changes in background diffusivity that spanned 3 orders of magnitude resulted in only a factor of 4 variation in salt flux, indicating only a modest dependence. The weak dependence of salt flux on the choice of background diffusivity is due to the localized nature of the salt flux as well as the tendency of the model to produce less stratification when subjected to higher diffusivities. Since salt flux is a product of both stratification and diffusivity, a simultaneous increase in diffusivity and decrease in stratification would tend to result in little change. So the lack of a strong relationship between salt flux and background diffusivity is not unexpected. 5. Conclusions [38] In April 2003, we injected Rhodamine-WT fluorescent dye into the halocline at the base of the Delaware River plume during a strong upwelling event. In this paper, we employed a numerical model of Delaware Bay and the adjacent coastal region that incorporates the Mellor-Yamada Level 2.5 turbulence closure scheme to simulate the observed dye injection event. [39] The model simulation was compared with observations at moorings as well as a number of transects and reveals that the model is able to satisfactorily reproduce the flow field simulating the bifurcation and subsequent advection of the dye tracer. Both observations and simulations show that the dye immediately bifurcated: One third of the 14 of 15

15 dye moved offshore with a portion of the plume, while the other 2/3 remained within the halocline, near the coast. The offshore patch was entrained in the across-shelf Ekman transport associated with the strong upwelling winds. The inshore patch remained within the portion of the plume that remained near the coast in relatively shallow water. The inshore patch was influenced by a combination of wind- and buoyancy-driven flow. The dye first moved onshore within the halocline because of upwelling circulation. It was then affected by the buoyant plume moving downshelf, whose combination of a strong halocline (which inhibited vertical mixing) and vertical shear (which transported any surface dye downshelf) resulted in the majority of the dye remaining within the halocline bounded by lower concentrations below and above. [40] Comparison of simulated and observed vertical mixing shows that the model accurately reproduced the observed mixing and accompanying vertical salt flux within the offshore plume. Simulated vertical viscosity and vertical salt flux were similar to observed values [Houghton et al., 2004]. Maximum values of salt flux were located near the seaward edge of the buoyant plume, in agreement with previous numerical and theoretical studies. However, the strong stratification (Ri > 0.25) associated with the inshore patch caused the closure scheme to abruptly shut off the turbulent eddy viscosities, leaving the circulation model dependent on arbitrarily chosen constant background values. Nevertheless, sensitivity analysis using background diffusivities ranging over 3 orders of magnitude (2 10 4,2 10 5, m 2 s 1 ) showed only a weak dependence of salt flux on the choice of background diffusivity. The weak dependence is due to the localized nature of the salt flux and the tendency of the model to produce less stratification in the presence of higher diffusivities. These results indicate that the Mellor Yamada turbulence closure scheme is able to adequately simulate salt flux and vertical mixing within those portions of the Delaware River plume characterized by Ri < 0.25, but the choice of background diffusivity plays a minor role in determining the mixing and stratification of those portions of the plume characterized by Ri > [41] While these results are encouraging, care must be taken in expanding this study to other cases of mixing within the coastal ocean. This study provided reasonable agreement between the simulation and observations over a 3-d time period, which is appropriate for the examination of wind-driven mixing. However, it may yield different results for longer timescales. Additionally, we examined the effects of mixing on salt flux. However, nitrates, oxygen, chlorophyll, and other nonconservative tracers tend to be characterized by larger vertical gradients than conservative tracers such as salt. Large changes in vertical diffusivity would tend to result in large variations in vertical flux of these tracers. [42] Acknowledgments. We would like to thank two anonymous reviewers for their insightful comments. This project was funded by the National Science Foundation through grant OCE to the University of Delaware, grant OCE to Columbia University (this is Lamont- Doherty Earth Observatory contribution number 7084), and a subgrant to the University of Georgia. References Austin, J. A., and S. J. Lentz (2002), The inner shelf response to winddriven upwelling and downwelling, J. Phys. Oceanogr., 32, Avicola, G. S., J. N. Moum, A. Perlin, and M. Levine (2006), Enhanced turbulence due to the superposition of internal gravity waves and a coastal upwelling jet, J. Geophys. Res., 112, C06024, doi: /2006jc Blanton, J. 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Res., 110, C03014, doi: /2003jc Whitney, M. M., and R. W. Garvine (2006), Simulating a coastal buoyant outflow: Comparison to observation, J. Phys. Oceanogr., 36, Willmott, C. J., S. G. Ackleson, R. E. Davis, J. J. Feddema, K. M. Klink, D. R. Legates, J. O Donnell, and C. M. Rowe (1985), Statistics for the evaluation and comparison of models, J. Geophys. Res., 90, R. W. Garvine, College of Marine and Earth Studies, University of Delaware, 101A Robinson Hall, Newark, DE 19716, USA. R. W. Houghton, Lamont-Doherty Earth Observatory of Columbia University, Route 9 West, Palisades, NY 10964, USA. C. E. Tilburg, Department of Chemistry and Physics, Marine Science Center, 11 Hills Beach Road, Biddeford, ME 04005, USA. (ctilburg@ une.edu) 15 of 15