Numerical simulations of the seasonal circulation patterns ... - CiteSeerX

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FISHERIES OCEANOGRAPHY

Fish. Oceanogr. 10 (Suppl. 1), 132– 148, 2001

Numerical simulations of the seasonal circulation patterns and thermohaline structures of Prince William Sound, Alaska Blackwell Science Ltd

JIA WANG,1,2,* MEIBING JIN,2 E. VINCENT PATRICK,3 JENNIFER R. ALLEN,4 DAVID L. ESLINGER,5 CHRISTOPHER N. K. MOOERS6 AND R. TED COONEY2 1

International Arctic Research Center–Frontier Research System for Global Change University of Alaska Fairbanks, Fairbanks, AK 99775 – 7335, USA 2 Institute of Marine Science, University of Alaska Fairbanks, Fairbanks, AK 99775 – 7220, USA 3 Computer Visualization Laboratory, University of Maryland, MD 20723, USA 4 Alaska Digital Graphics, Anchorage, AK 99521–2806, USA 5 NOAA Coastal Service Center, 2234 South Hobson Avenue, Charleston, SC 29405 – 2413, USA 6 Rosentiel School of Marine at Atmospheric Science, University of Miami, Miami FL 83149, USA

ABSTRACT A three-dimensional, primitive-equation ocean circulation model was applied to Prince William Sound, Alaska (3D-PWS circulation model), under forcing of an ocean tide, freshwater runoff, surface heat flux, Alaska Coastal Current (ACC) throughflow (inflow/outflow), and daily (synoptic), spatially varying winds. The 3D structures and seasonal cycles of the circulation patterns, temperature, salinity (density), and mixed layer are examined. Freshwater runoff significantly contributes to the basin-scale cyclonic circulation, which was not addressed in the previous simulations. Two typical circulation regimes, cyclonic and anticyclonic, characterize the complex flow patterns that depend on the intensities of the ACC thoughflow, freshwater discharge, and the synoptic wind. The spring (April–May) circulation pattern is characterized by a weak (maximum current 0.1 ms–1) anticyclonic flow in the central Sound, while the autumn (September– October) circulation is dominated by a basin-scale, cyclonic gyre (maximum current 0.2 ms–1) due to the increase of the ACC throughflow and the maximum freshwater influence. During the summer, the circulation includes the cyclonic and anticyclonic gyres. During the winter, the circulation pattern is controlled by the basin-scale cyclonic gyre and surface drift driven by the strong north-easterly (south-westward) wind forcing. The seasonal cycles of temperature (T) and salinity (S) *Correspondence. e-mail: [email protected]

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vs. depth compare well with the observations. The simulated spring and autumn surface circulation patterns compare qualitatively well with the towed ADCP (acoustic Doppler current profilers) flow patterns and dynamic height patterns in the central Sound. An application of this model to zooplankton overwintering is discussed. Key words: numerical simulation, thermohaline structure, freshwater runoff, overwintering INTRODUCTION Prince William Sound (PWS) is a combination of multiple deep basins, fjords, channels, islands, inlets, and estuaries along the alpine coast of southern Alaska (Fig. 1). PWS is very rich in the production of salmon, halibut, herring, and other fish species. Its economic potential strongly depends on how well the fish catch can be managed and how well the marine pollution can be minimized in the presence of a major oil tanker route. Both the marine ecosystem and oil spill dispersion depend upon the variable circulation of PWS. Therefore, knowledge of the seasonal circulation patterns is essential to understanding the PWS ecology and estimating environmental risks due to oil spills. The SEA (Sound Ecosystem Assessment) Program conducted multidisciplinary, ecosystem and physical oceanographic observations in PWS (Cooney et al., 2001; this volume p. 1). The numerical model simulations described here were implemented to assist in understanding the PWS circulation over a seasonal cycle. This paper presents numerical simulations of the PWS seasonal circulation and thermohaline structures to depict typical flow (circulation) regimes, and to understand the PWS circulation under forcing of seasonal heating/cooling, freshwater runoff, realistic (seasonal and synoptic) wind fields, and ocean tides, in comparison with available observations. Thus, this study offers, for the first time, a 3D view of the PWS seasonal circulation patterns and thermohaline structures under all available forcings: freshwater runoff, orographically influenced wind fields, Alaska Coastal Current (ACC) throughflow (volume transport and T and S fluxes), surface heat flux, and ocean tides. The seasonal 3D circulation patterns and the thermohaline structures were not well described and understood previously because there had been insufficient observations (Muench and Schmidt, 1975; Schmidt, 1977; Niebauer © 2001 Blackwell Science Ltd.

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Figure 1. (a) The study area with an orographic view of terrain and water depth and (b) bottom topography of Prince William Sound (depths in metres). The nine meteorological stations over the Sound are indicated by the stars. The west-to-east transect is also indicated for the plots shown in Figs 10 and 11.

et al., 1994), no sophisticated 3D circulation model existed, and also because the external oceanic and atmospheric forcings were not well known. Mooers and Wang (1998) implemented a 3D-PWS circulation model and conducted simulations using idealized wind forcing and fixed throughflow (0.3 Sv, 1 Sv = 106 m3 s–1), without surface heat flux and freshwater discharge. Under these conditions, the major circulation pattern was dominated by the cyclonic throughflow from Hinchinbrook Entrance to Montague Strait (see Fig. 1). Due to the lack of freshwater runoff, the basin-scale cyclonic circulation was not obtained. Mooers and Wang (1998) also performed some sensitivity studies on (i) throughflow magnitude, (ii) wind direction (blowing from four different directions), and (iii) buoyancy flux (fresh surface water)

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intrusion through Hinchinbrook Entrance from the Gulf of Alaska (GOA). These sensitivity analyses indicated that the throughflow is the most important boundary forcing determining the circulation pattern and intensity inside the Sound, while the wind-forcing can be important in modifying the surface circulation pattern when the throughflow is weak. Thus, wind-forcing is secondary compared with the strong throughflow. The results of the sensitivity study suggest that all atmospheric and oceanic forcings are necessary to simulate accurately the seasonal variations of circulation patterns and thermohaline structures. The model performance was encouraging under idealized forcing and demonstrated a consistency between the model and another two-compartment model in a study of the tracer transport experiments (Deleersnijder et al., 1998). Wang et al. (1997) used the same model to simulate PWS tides under ocean tide forcing from six constituents and throughflow. The tide type factor, F = (K1 + O1)/ (M2 + S2), is 0.5, indicating a mixed, mainly semidiurnal tide type. The preliminary results indicated that the tidal currents are of the same order of magnitude as the nontidal currents (density- and wind-driven) in the southern Sound and that an anticyclonic tidal residual current can be generated in the central Sound and north-western Sound. Although the tidal dynamics are not discussed here, tidal mixing (Wang et al., 1999a) is included in the present model using the predominant M2 tide only. Wang et al. (1999b) conducted a seasonal simulation of ocean circulation patterns using climatological atmospheric-forcing and freshwater as a line source, but without tidal forcing. The preliminary results can capture a reasonable seasonal cycle. However, no detailed 3D structure of the circulation and thermohaline structures were shown, and no model–data comparison was conducted. The purpose of this study is to: (i) simulate the PWS seasonal circulation patterns under atmospheric-forcing, coastal inflow/outflow-forcing, and ocean tidal-forcing using a sophisticated 3D numerical model; (ii) examine the seasonal variations of the thermohaline structures, which are essential for understanding the ecosystem variability in the Sound; and (iii) compare the model simulations with some of the observations made during the SEA Program. We will leave the sensitivity study to a later study for investigation of the forcing factors; such as, orographic wind fields, freshwater runoff as a line source, and the ACC throughflow, which are the key scientific issues in the GOA region. First, we will summarize the 3D numerical model and its set-up (model parameters, initial and boundary conditions). Second, we describe the seasonal forcing functions. Third, we present the seasonal simulation results: general circulation (wind- and density-driven circulation, mesoscale features, etc.) and temperature and salinity structures,

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with comparisons with the observations. Fourth, we present an application of the simulations to zooplankton overwintering and, fifth, we summarize the results.

A modified version (Wang and Ikeda, 1996) of Blumberg’s (1991) ECOMSI (Estuarine and Coastal Ocean Model with Semi-Implicit) scheme using a semi-implicit scheme without mode-splitting is utilized with a newly implemented predictor-corrector scheme for the time integration by Wang and Ikeda (1996, 1997a). This version was implemented for PWS by Mooers and Wang (1998). It is based on the primitive equations with hydrostatic and Boussinesq approximations and has the following features as the Princeton Ocean Model (POM, Mellor, 1991): (i) horizontal curvilinear coordinates (not used in PWS); (ii) an Arakawa C grid; (iii) sigma (terrainfollowing) coordinates in the vertical with realistic bottom topography; (iv) a free surface; (v) a level 2.5 turbulence closure model for the vertical viscosity and diffusivity (Mellor and Yamada, 1982); (vi) a mean flow shear parameterization for horizontal viscosity and diffusivity (Smagorinsky, 1963); (vii) a semi-implicit scheme for the shallow water equations (Blumberg, 1991); and (viii) a predictor-corrector scheme for the time integration to avoid inertial instability (Wang and Ikeda, 1996, 1997a). The model equations are as follows (with notations referred to Wang and Ikeda, 1996): ∂u 1 ∂p ∂ ∂u + L(u) − fv = − + (K M ) + Fx , ∂t ρo ∂x ∂z ∂z

(1)

∂v 1 ∂p ∂ ∂v + L(v) − fu = − + (K M ) + Fy , ∂t ρo ∂y ∂z ∂z

(2)

∂p , ∂z

(3)

∂u ∂v ∂w + + = 0, ∂x ∂y ∂z

(4)

∂θ ∂ ∂θ + L(θ) = (K H ) + F θ, ∂t ∂z ∂z

(5)

where θ denotes both temperature and salinity, L(α) = ∂(uα)/ ∂x + ∂(vα)/ ∂y + ∂(wα)/ ∂z, and ∂ ∂u ∂ ∂u ∂v Fx = (2A M ) + [ A M( + )], ∂x ∂x ∂y ∂y ∂x ∂ ∂v ∂ ∂u ∂v Fy = (2A M ) + [ A M( + )], ∂y ∂y ∂x ∂y ∂x ∂ ∂θ ∂ ∂θ Fθ = (A H ) + (A H ), ∂x ∂x ∂y ∂y

∂u 2 ∂v 2 1 ∂u ∂v 2 1/ 2 ) +( ) + ( + ) ] , ∂x ∂y 2 ∂y ∂x (7) where CHOR is a nondimensional constant (set to 0.2 in this study). Vertical viscosity (KM) and diffusivity (KH) coefficients are calculated using the level 2.5 turbulence closure model (Mellor and Yamada, 1982). The time-integration scheme in this modified version uses the Euler forward predictor-corrector scheme (Wang and Ikeda, 1996, 1997a). A predictor step and a corrector step are applied to Equations (1) and (2) as follows: A M = A H = CHOR ∆x∆y [(

THE 3D-PWS CIRCULATION MODEL

ρg = −

where the horizontal viscosity (AM) and diffusivity (AH) coefficients are assumed equal and parameterized by the Smagorinsky (1963) formula as follows:

n u n+1 − u n + Ln (u) − fv = RHSn , ∆t

(8)

n v n+1 − v n + Ln (v) + fu = RHSn , ∆t

(9)

for the predictor step, and u n+1 − u n + Ln (u) − f [βv n+1 + (1 − β)v n ] = RHSn , ∆t (10) v n+1 − v n + Ln (v) + f [βu n+1 + (1 − β)u n ] = RHSn , ∆t (11) for the corrector step, with β ≈ 0.5 + (f∆t)2/8 to maintain a neutral amplitude of the inertial wave, where RHS denotes all terms on the right-hand side of the equation. A detailed discussion of the inertial stability analysis of several well-known ocean general circulation models has been given by Wang and Ikeda (1997a). The importance of using the predictor-corrector scheme is to avoid the inertial instability caused by the Euler forward scheme used in the original ECOMSI by Blumberg (1991) and to improve the phase error that allow correct simulation of inertial-gravity waves. To simulate the transport of passive tracers (pollutants, biological particles, chemical substances, etc.; Eslinger et al., 2001; this volume p. 81), the following 3D concentration transport model has been added to the 3D-PWS model: ∂C ∂ ∂C + L(C) = (K H ) + FC − TD C + Qsource _ Qsink , ∂t ∂z ∂z (12)

(6)

where C is the concentration of the passive tracer, TD is the decay time scale for C, KH is the vertical diffusivity calculated from the Mellor–Yamada level 2.5 turbulence closure model (Equation 7), and Fc is the horizontal

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Figure 2. The time series of (a) inflow from the Hinchinbrook Entrance: the solid line is from Niebauer et al. (1994) and dashed line is from the SEA observations (Vaughan et al., 1997), (b) heat flux from COADS, and (c) freshwater runoff (Simmons, 1996).

diffusivity term whose diffusivity coefficient is calculated from the Smagorinsky parameterization, defined similarly to the temperature and salinity diffusivity terms. The source and sink terms, Qsource and Qsink, and the decay term (TDC) for the variables of interest (e.g. biological species, fish larvae, pollutants, etc.) on the right-hand side of (Equation 12) are utilized in the application of the 3D-PWS model to zooplankton. The surface boundary conditions are defined as follows: ρo K M(

∂u ∂v , ) = (τx , τ y), ∂z ∂z

(13)

for the wind stresses and ∂T )= ∂z ∂S K H( ) = ∂z

K H(

(

QH ) + C(Tabs − T), ρCP

(14)

QS + C(Sabs − S),

for the heat and salt (freshwater or mass) fluxes following Wang et al. (1994), where ρ and CP are the water density and specific heat of water (4187 Jkg–1 K–1), respectively, and C is the restoring time constant (5.79 × 10 – 6 ms–1), whose reciprocal gives a restoring time scale of 2 days for a unit thickness of water, i.e. T and S in the upper 15-m

surface layer adjust to their respective observed values on a time scale of 30 days. QS (ms–1) is the E–P (evaporation minus precipitation) or the salt flux, while precipitation includes rainfall and freshwater runoff as shown in Fig. 2(c). Similarly, QH (Wm–2) is the net surface heat flux calculated from the conventional shortwave and longwave radiative heat fluxes and sensible, and latent heat fluxes. The model domain includes the entire PWS with two open boundaries at Hinchinbrook Entrance and Montague Strait (Fig. 1), allowing water exchange with the Alaskan coastal waters, as in Mooers and Wang (1998). The model grid spacing is 1.2 km, which is eddy-resolving because the internal Rossby radius of deformation is about 5 km in winter (50 km in summer, Niebauer et al., 1994). There are 15 vertical sigma levels, with a relatively high resolution in the upper 50 m to resolve the upper mixed layer. The integration time step is 100 s which is about 10 times the CFL (Courant–Friedrichs–Lewy) constraint because the semi-implicit scheme has been used for the shallow water equations (Wang et al., 1994). The initial temperature and salinity fields used are based on a typical spring profile (Fig. 2, dashed line, Mooers and Wang, 1998) observed in the central Sound in March 1995 (T/S ranges from 4°C/31.2 psu at the surface to about 6°C/ 32.3 psu at 400 m) and were specified to

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Figure 3. The 1996 time series of daily wind velocity vectors at (a) mid-Sound, (b) Potato Point, (c) Valdez, and (d) Whittier. The thick solid line with the dot (to which the winds blow) denotes the annual mean wind velocity. The locations are indicated in Figure 1(b).

be horizontally uniform. The model was spun-up for 1 year from these initial conditions under seasonal forcing as described in the next section to reach a dynamical and thermodynamical seasonal cycle; i.e. the seasonal cycle has been built up. The restart file was saved for use as the initial condition for the prognostic runs. Vertical viscosity diffusivity (which are set equal) were determined at each time step and each grid point from the Mellor–Yamada 2.5 turbulence closure model with a background viscosity of 10–5 m2 s–1 (i.e. this value is used if the calculated values are smaller than this specified value). Horizontal viscosity and diffusivity (which are set equal) are determined from the Smagorinsky parameterization with the nondimensional coefficient, CHOR in (Equation 7) is set equal to 0.2; the typical computed horizontal viscosity is about 5–10 m2 s–1. SEASONAL FORCINGS AND BOUNDARY CONDITIONS According to observations at Hinchinbrook Entrance (Niebauer et al., 1994), the coastal inflow varies seasonally (Fig. 2a). The outflow through Montague Strait is virtually the same, although the water volume in the Sound may increase or decrease over limited periods in response to transient forcing. The transport during the SEA program during 1995–96 was also calculated (dashed line of

Fig. 2a). Hence, the inflow of the 1995–96 observations was specified over the seasonal cycle through Hinchinbrook Entrance, while a radiation boundary condition for the normal velocity (with self-adjusted outflow of the same amount as the inflow) was applied to Montague Strait. The inflow and outflow were assumed maximum at the surface and linearly decrease to zero at 200 m or at the bottom. This inflow and outflow were boundary condition was applied uniformly across the openings to the 3D velocity grid points, while its (vertical and lateral) integration must be equal to the observed volume transport, following Wang et al. (1994). The open boundary condition at Montague Strait for temperature and salinity is free-advective; i.e. the model determines the mass field there, while at Hinchinbrook Entrance, the CTD-observed T and S profiles during 1995–96 (Vaughan et al., 1997) were specified over the seasonal cycle. The boundary condition for the 3D velocity conserves the volume transport balance, i.e. the outflow at Montague Strait is specified to equal the inflow from Hinchinbrook Entrance. The M2 tide harmonic constants for amplitude and phase (Schwiderski, 1980) are prescribed for the surface elevation at both Hinchinbrook Entrance and Montague Strait (Wang et al., 1997). The monthly surface net heat flux (Fig. 2b) originating from the COADS (Comprehensive Oceanic and

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Figure 4. The snapshots of the wind velocity fields derived from the empirical wind-fetch interpolation on days 15 (a, January), 105 (b, spring), 195 (c, July), and 285 (d, October). The red arrows denote the observed wind vectors.

Atmospheric Data Sets) was applied uniformly in PWS, together with the restoring surface temperature boundary condition to the CTD-observed seasonal SST during 1995–96 (Vaughan et al., 1997). The monthly freshwater runoff (Fig. 2c) that was calculated from the hydrological Digital Elevation Model (DEM, Simmons, 1996) was specified uniformly at the surface of PWS as a rate of precipitation (with units of ms–1), together with the restoring boundary condition to the

CTD-observed seasonal SSS during 1995–96 (Vaughan et al., 1997). This combination is an effective way to physically describe freshwater runoff-forcing as a line source along the coast, similar to Wang et al. (1994). There exist several ways to prescribe the freshwater input to an ocean: (i) Using specified salinity at the coast plus the continuity equation to estimate the vertical motion (Oey, personal communication); (ii) using river flux/discharge (m3 s–1) at a river mouth plus riverine salinity (Oey et al., 1985; Wang

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Figure 5. The 3D-PWS model simulated surface circulation patterns on days 15 (a, January), 105 (b, April), 195 (c, July), and 255 (d, September).

et al., 1999a); and (iii) expressing freshwater flux/discharge (m3 s–1) in terms of equivalent precipitation (ms–1) at all model grid points plus the sea surface salinity restoring condition to produce a freshwater input of a line source into an ocean with numerous small creeks and streams along the coast, such as in PWS (Wang et al., 1994, 1999b). The wind-forcing, one of the most difficult forcing functions in the study area to characterize, is highly spatially variable over PWS due to orographic effects, and strongly seasonal with synoptic time scales of days to weeks. Threehourly records of the wind speed and direction, humidity, air temperature, and shortwave solar radiation were acquired at nine meteorological stations within PWS (Fig. 1b).

These observations confirm that the wind speed and direction are highly spatially variable among stations (Fig. 3). The mid-Sound station (Fig. 3a) is unobstructed by coastal orography, and the winds vary over a full range of direction with time. However, at Potato Point (Fig. 3b) located in lower Valdez Arm where the winds are channelled by high mountains on both sides, the wind direction is either south-westward or north-eastward. Furthermore, the wind speed there is the highest among the nine stations. Thus, its annual average wind is south-westward at a speed of 6–7 ms–1. At Valdez (Fig. 3c), the wind is also channelled by mountains, almost equally north-easterly and south-westerly; thus, the annual average is nearly

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zero. In contrast, at Whittier (Fig. 3d), south-westerly winds dominates, occasionally with north-easterly; the annual mean south-westerly wind is about 3 ms–1. Since the orographic effects on the wind field over PWS are significant, in principle, a mesoscale meteorological model is needed to calculate the surface wind field. For a first approximation, however, an empirical interpolation scheme (nine wind subregions responding to 16 possible prevailing wind directions) was used to interpolate and extrapolate the wind records at the nine stations to cover the entire PWS following Wang et al. (1999b). Figure 4 demonstrates the daily mean wind fields on Julian days 15 (January), 105 (April), 195 (July) and 285 (October). Spatially variable features are obvious that cannot be captured by wind records at a single station. The interpolated wind vectors compare reasonably well with the observed vectors (in red). Note that there are sharp changes along boundaries between neighbouring regions; however, this method provides a first estimate of the spatially variable wind fields, albeit with exaggerated large wind stress curls and divergences. We also conducted the simulation using only mid-Sound wind stress (meteorological station). The circulation pattern in central Sound was similar; but the circulation in the Valdez Arm and those in other estuaries are different when the prevailing orographically steered winds were considered. This topic should be studied further.

SEASONAL CIRCULATION, TEMPERATURE AND SALINITY PATTERNS Surface circulation, temperature and salinity patterns The surface (3 m) circulation patterns in mid-January (Fig. 5a), April (Fig. 5b), July (Fig. 5c), and September (Fig. 5d) are discussed, along with the sea surface temperature (SST, Fig. 6) and sea surface salinity (SSS, Fig. 7) fields. There is a basin-scale, cyclonic circulation (Fig. 5a) in January with outflow through Knight Island Passage and Montague Strait, indicating a high flushing rate. The January SST pattern is rather uniform in space, ranging from 3 to 5 °C, with the eastern Sound being warmer than the western Sound (Fig. 6a). The January SSS pattern (Fig. 7a) has two regimes: high salinity in the central and eastern Sound (~30.5 psu) and low salinity in the north-western Sound (~28.5 psu), indicating a more significant oceanic influence in the central and eastern Sound than in the western Sound. When a minimum throughflow of GOA water occurs in April, a weak (maximum 0.1 ms–1) anticyclonic circulation occurs in the central Sound (Fig. 5b). This anticyclonic gyre was captured by the towed ADCP-observed velocity field in April 1995 (see Fig. 4 of Vaughan et al., 2001;

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this volume p. 58). The April SST (Fig. 6b) increases to about 5°C in the central Sound and to about 6°C in the western Sound due to solar warming and freshwater inflow that is usually warmer than the Sound SST. The April SSS reflects that freshening first builds up along the north-western coasts and estuaries (Fig. 7b), and later over the entire Sound after the spring freshwater discharge. In July, the surface circulation pattern (Fig. 5c) is dominated by an anticyclonic gyre in the central Sound. There is a northward or north-eastward flow through Knight Island Passage and Montague Strait, opposite from the January flow (Fig. 5a). This north-eastward current along the west coast is generated by the south-easterly winds (see Fig. 4c) and inflow from Montague Strait (because there is net outflow through Hinchinbrook Entrance during July and August, see Fig. 2a, dashed line). As freshwater runoff continues freshening PWS and the south-easterly wind dominates, the circulation pattern is relatively complicated, including an anticyclonic gyre in the central Sound (Fig. 5c). The July SST increases to a maximum value of 13°C (Fig. 6c), and the July SSS indicates freshwater plumes from Valdez Arm and the northern coast being advected to the south (Fig. 7c). The circulation pattern in September (Fig. 5d) and October (not shown, but similar to September) is dominated by a basin-scale, cyclonic gyre due mainly to the increase in throughflow (Fig. 2a) and the maximum freshening during August–September (Fig. 2c). The north-easterly wind-driven current dominates in the northern Sound. In the central Sound, the enhanced throughflow through Hinchinbrook Entrance drives the cyclonic circulation in September (Fig. 5d) and October (not shown, but similar to September). This cyclonic circulation pattern was consistent with the computed surface dynamic height (see Fig. 10 of Vaughan et al., 2001; this volume p. 58). The oceanic intrusion into the Sound is evident in SST (Fig. 6a) and SSS (Fig. 7a) fields, because the ACC transports warmer and more saline water into PWS. Hence, strong SSS gradient (salinity front) occurs with a south-west–north-east orientation (Fig. 7a–c). The maximum freshening of the western Sound occurs in autumn (Fig. 7d). Seasonal cycles of T and S vs. depth The simulated seasonal cycles of temperature and salinity vs. depth in the central Sound (north of mid Sound station) are described (Fig. 8). In winter, temperature and salinity are relatively uniform in the upper 100 m because of strong vertical mixing. In spring, solar warming and freshening form strong stratification in the upper layer. In summer, upper layer stratification increases. In autumn, cooling starts at the surface and penetrates

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Figure 6. Same as Figure 5, except for the surface sea temperature (SST).

downward due to vertical mixing. The upper mixed layer forms in autumn and is persistent through winter to spring. The observed seasonal cycles of T and S averaged over 1990–94 at C-LAB (Communication-Linked Automated Buoy) or station CFOS-13 (Cooperative Fisheries and Oceanographic Studies, west of mid-Sound station, Fig. 9) in the central Sound have similar structures, phases and magnitudes compared to the simulations (Fig. 8). However, the simulated salinity is 1 psu lower than the 4-year mean, probably because the initial salinity used in the model of 1996 was fresher than the observations during 1990–94. Nevertheless, the pattern is quite promisingly similar. Sectional distributions Salinity and normal velocity distributions for April and September along a west-to-east transect (cf. Figure 1) are examined (Fig. 10). In April, freshening starts in the

western Sound, while the eastern Sound is still saline. In September, both sides of the Sound are covered by a freshwater layer with freshwater thickness greater on the western side. In the central Sound, the haline structure is bowl-shaped or concave-upward (Fig. 10a) in April (indicating an anticyclonic gyre as shown in Fig. 5b), and is dome-shaped or concave-downward (Fig. 10b) in September (indicating a cyclonic circulation as shown in Fig. 5d). The bowel-shaped structure in April and dome-shaped structure in September is clearly reflected in velocity transects (Fig. 11). In the central Sound, the April anticyclonic gyre penetrates to the bottom (Fig. 11a) with a maximum speed of 0.1 ms–1. The September cyclonic gyre (Fig. 11b) is stronger (maximum speed of 0.2 ms–1). Vertical and horizontal velocity shears are moderate in both April and September, indicating baroclinic and barotropic instabilities might occur (Wang and Ikeda, 1997b).

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Figure 7. Same as Figure 5, except for the surface sea salinity (SSS).

Furthermore, small eddies are evident for both April and September in the western Sound. Volume transport: seasonal variation Whether the ‘river/lake-like’ circulation regime prevails in PWS is one of major scientific hypotheses of the SEA Program. A high/low flushing flow due to the ACC throughflow and wind-driven flow was hypothesized to significantly influence the biomass pattern/ distribution and timing. During the high throughflow regime period, the biomass retention time scale is shorter in the Sound, and vice versa (Cooney et al., 2001; this volume p. 1). The streamfunction (depth-integrated volume transport) is a measure of the circulation in PWS. In April (Fig. 12a), an anticyclonic gyre exists in the central Sound and an elongated cyclonic gyre in the northern Sound. This regime is called the lake-like circulation scenario because

there is little exchange between PWS and GOA. In September (Fig. 12b), a strong cyclonic gyre exists in the central Sound and strong outflow through Montague Strait indicate a strongly advective regime. This regime may be regarded as the river scenario because of the enhanced exchange between PWS and GOA, due to the ACC throughflow. The winter circulation (Fig. 5a) has a similar character. These two regimes are considered very important in determining ecosystem variability in the Sound. Mesoscale dynamics related to ACC throughflow forcing To understand better the mesoscale dynamics (i.e. eddy development and decay), the time series of total kinetic energy (TKE), zonal kinetic energy (ZKE), and eddy kinetic energy (EKE) of the entire PWS domain (Fig. 13a) are used to interpret the seasonal variations, with TKE = ZKE + EKE, and TKE, ZKE, and EKE defined as follows:

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Figure 8. Simulated seasonal cycles of temperature (a) and salinity (b) vs. depth at station near the mid-Sound (see the location in Figure 1a).

IM JM KB

TKE = ZKE = EKE =

∑ ∑ ∑ρijk

u2ijk + v2ijk

i =1 j =1 k =1

2

IM JM KB

2 u2ijk + v ijk

i =1 j =1 k =1

2

IM JM KM

u′ijk2 + v ′ijk2

i =1 j =1 k =1

2

∑ ∑ ∑ρijk ∑ ∑ ∑ρijk

∆Vijk , ∆Vijk ,

(15)

∆Vijk ,

where IM

IM

i =1

i =1

(u jk , v jk ) = [∑(u ijk , v ijk )∆x ijk ] / ∑∆x ijk , (u′ijk , v ′ijk ) = (u ijk − u jk ′ v ijk − v jk ), ∆Vijk = ∆x ijk ∆yijk ∆ z ijk ,

(16)

IM, JM, and KB are the grid numbers in the x (subscript i), y (j), and z (k) directions, respectively, and ρ is the water density. ZKE (which is about three times smaller than EKE) represents the strength of the throughflow (Fig. 2a) and the density-driven flow (which peaks in August–September). For instance, ZKE is low from April through August, during which time the throughflow is weak and freshwater runoff increases. In September, the throughflow increases and the freshwater runoff reaches its maximum, leading to a basin-scale cyclonic circulation in the Sound. As a result, ZKE increases sharply in September. Thus, ZKE represents the strength of the basin-scale gyre or throughflow circulation. Another significant ZKE peak occurs during February and March during which there is an increased throughflow.

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Figure 9. The 5-year averaged (1990– 94) seasonal cycles of temperature (a) and salinity (b) vs. depth at station CFOS-13 (see the location in Figure 1b).

Figure 10. Simulated salinity distribution along the westto-east transect (Figure 1). (a) April and (b) September.

Figure 11. Similar to Figure 10, except for north–south velocity (v). (a) April and (b) September.

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Figure 12. The 3D-PWS model simulated streamfunction (transport) in April (a) and September (b). The enclosed solid / dashed lines denote the cyclonic / anticyclonic circulation.

Figure 13. The time series of the 3D-PWS model simulated TKE (solid line), ZKE (short dashed line with ‘Z’), and EKE (long dashed line with ‘E’) (a), and the mesoscale eddy growth rate (b) with the thick line being the 3-day moving average. © 2001 Blackwell Science Ltd., Fish Oceanogr., 10 (Suppl. 1), 132– 148.

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Figure 14. PWS zooplankton overwintering simulation: (a) The larvae release grid points under 400 m on February 1, 1996 [the solid line denotes the transect shown in (c) and (d)]; (b) Time series of the total number of zooplankton with time (note that the vertical axis is in logarithm, therefore the linear decrease means an exponential decay); A transect (at 60.75°N) view of the zooplankton distribution on (c) February 11 and (d) April 1; A plan view of the zooplankton distribution on (e) April 21 and (f) June 11.

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The strength of the mesoscale eddies can be measured by EKE and the growth rate (Fig. 13b). The eddies are usually generated by baroclinic instability of a current system due to strong vertical shear (Wang and Ikeda, 1997b). But, in PWS, the higher EKE is accompanied by the higher ZKE, suggesting that the stronger basinscale gyres are the sources of the mesoscale eddies due to transient (thoughflow) boundary forcing interacting with the topography. This differs from the baroclinic instability in a simple channel model of Wang and Ikeda (1997b), because in baroclinic instability, ZKE usually provides energy to EKE, i.e. ZKE depletes its energy (decrease in ZKE) to EKE (increase in EKE). EKE is about three times larger than ZKE because the active mesoscale eddies and transient currents dominate the mean flow. The positive/negative values (alternating signs) of the growth rate indicate the developing/decaying phase of eddies (Fig. 13b, thick line). The eddy duration time scales are from weeks to two months, based on the growth rate time series. AN APPLICATION OF THE 3D-PWS MODEL TO ZOOPLANKTON Zooplankton overwinter in PWS as an annually repeating phenomenon (Cooney et al., 2001; this volume p. 1), Neocalanus spp. (Copepoda) migrates to depths of 400 m or deeper in early summer where they drift passively until spawning and drying in January or February. The resulting eggs and Nauplii rise to the surface waters. A modelling experiment was designed to examine the effects of horizontal advection on the surface distribution of Copepodites during spring. Simulated Neocalanus were released at 400 m over a 1-month period beginning on 1 February (source term in Equation 12; Fig. 14a). A rise rate of 400 m per month was specified to bring the first Copepodites to the surface by 1 March as observed in field collections (Cooney et al., 2001; this volume p. 1; Fig. 14c), and for 30 days thereafter (Fig. 14d). A daily mortality rate of 6% (C in Equation 12) accounted for natural losses, and modelled animals were also allowed to be swept from the model domain by horizontal current advection. The vertical and horizontal distributions and numbers of modelled Neocalnus were then tracked over time (Fig. 14c,d) and then horizontal advection (Fig. 14e,f). In the early modelled upward migration (1 February–1 April), there was a tendency for Neocalanus to be advected slowly toward Hinchinbrook Entrance with the deep outflow. However, as the modelled Copepods reached the upper layers, they were carried back into the Sound by surface inflow. In April, the anticyclonic circulation (Fig. 5b) dominating the Sound at that time, advected

the modelled Copepods northward and north-westward (Fig. 14e). By 11 June, most survivors were located in the westward regions of PWS and in Montague Strait (Fig. 14f). It is here that juvenile pink salmon originating from hatcheries and wild natal areas feed before migrating out of the Sound. This experiment demonstrated that: (i) Under conditions of circulation simulated for 1996, some Neocalanus arising from local populations are retained in PWS for sufficient time to grow in the surface layers and form a portion of the forage base used by juvenile salmon and other planktivores in the spring (Fig. 14b); and (ii) in a qualitative sense, the resulting distributions in north and west regions agree with field observations of Neocalanus obtained by nets and high-frequency acoustics (Kirsch et al., 2000) in May, 1996. CONCLUSION AND DISCUSSION The 3D-PWS circulation model reveals important seasonal dynamics of PWS. The simulation produced consistent seasonal circulation patterns under forcing of the throughflow, freshwater runoff, monthly mean heating, daily (synoptic) winds, and the M2 tide. The circulation patterns vary seasonally mainly due to the seasonal variability of the throughflow and the highly varying wind fields. Anticyclonic circulation patterns are most likely to occur during the period of low freshwater runoff, weak throughflow, and weak north-east winds (April conditions), while cyclonic circulation patterns dominate during the period of high throughflow and high freshwater runoff (September–October through the winter season). Sensitivity studies are obviously needed to investigate the contribution of each forcing factor to these circulation patterns. A ‘lake-like’ scenario is characterized by the April anticyclonic circulation due to minimum throughflow from ACC. A ‘river-like’ scenario is characterized by September to winter season due to maximum ACC throughflow (inflow via Hinchinbrook Entrance and outflow via Montague Strait). At the same time, northerly winds generate the surface current that flows through Knight Island Passage and out Montague Strait. The most energetic river-like scenario occurs in the winter months (from November to January), due to both strong throughflow and persistent north-east winds controlled by the persistent Aleutian Low. Qualitatively consistent seasonal cycles of temperature and salinity were reproduced using monthly heat flux and freshwater runoff as a line source. Not only are the seasonal SSS and SST patterns reproduced (due to the relaxation to climatology constraint), but also the vertical structure. The thermal and freshwater

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forcing are essential in producing the deep winter mixed layer (about 100 m) and the shallow summer stratified layer. Strong mesoscale variability with a seasonal cycle characterizes the PWS circulation. In particular, the monthly eddy kinetic energy (EKE) is highly (positively) correlated with the throughflow at Hinchinbrook Entrance. External wind-forcing may also trigger the development of the mesoscale eddies. What type of instability (baroclinic, barotropic, or mixed) that are likely to occur in such a basin with complex geometry and topography is an important topic that is beyond the scope of this study. An application of the 3D circulation model to questions about the relationship between seasonally varying current structure and the distributions of large calanoid copepods demonstrates linkages to the feeding ecology of juvenile pink salmon, and possibly juvenile herring. This demonstration points to the necessity for eventually coupling physical model with a biological model. Eslinger et al. (2001; this volume p. 81) describe a plausible linkage with wind-forced vertical mixing processes in the surface water that ties primary productivity and food-web transfer to seasonally varying upper-layer stability and nutrient supplies. The wind fields are another important forcing element in the seasonal circulation in PWS. Its highly spatially variable direction and magnitude due to orographic effects are a topic for future research. Nevertheless, the present empirical interpolation scheme for the wind field provided a first step for use in calculating the seasonal circulation (Wang et al., 1999b). The tidal residual currents (Wang et al., 1997) may be another important contribution to the PWS circulation patterns. In summary, systematic sensitivity studies of these external forcings are essential to understand the contribution (by percentage) of each forcing to the seasonal cycle of the circulation, temperature, and salinity patterns. ACKNOWLEDGEMENTS The SEA Program of the Exxon Valdez Oil Spill (EVOS) Trustees Council and the Oil Spill Recovery Institute (OSRI) supported this research awarded to JW. Jia Wang acknowledges support from the International Arctic Research Center-Frontier Research System for Global Change (IARC-FRSGC) for providing the computer power and from Prof M. Ikeda of Hokkaido University, Japan, for his helpful discussions of the mesoscale ocean dynamics. We sincerely appreciate the two anonymous reviewers for their very constructive comments that helped greatly improve the paper, and the guest editor, Dr William Pearcy, for his editorial assistance.

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