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An eddy-resolving model of circulation on the western Gulf of Alaska shelf. 2. Comparison of results to oceanographic observations

P. J. Stabeno

Pacific Marine Environmental Laboratory, NOAA, Seattle, Washington

A. J. Hermann

Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle
(Also at Pacific Marine Environmental Laboratory, NOAA, Seattle, Washington)

Journal of Geophysical Research, 101(C1), 1151-1161 (1996).
Copyright ©1996 by the American Geophysical Union. Further electronic distribution is not allowed.

Abstract

Currents generated by an eddy-resolving, semispectral primitive equation model are compared with those measured by moored current meters (1989 and 1991) and satellite-tracked drifting buoys (1987) from Shelikof Strait, Alaska. The model reproduced many of the dominant circulation features, including the cross-sectional spatial structure of the Alaskan Coastal Current, the estuarine inflow at the bottom of the sea valley, and the mean transport. The first-mode empirical orthogonal functions of the model and of the observed data represent similar spatial structures and were significantly correlated in time. While the model produced eddies (>20-km diameter) at a similar rate as observed, the timing did not generally match the observations. As a result, correlations between the measured currents and model-generated currents usually were not significant. Correlations between modeled and measured transport through the sea valley, however, were significant for both years.

 

Introduction

The Alaskan Coastal Current (ACC) is typically a narrow (<30 km), shallow (<150 m), and mainly baroclinic flow [Schumacher and Reed, 1980]. It extends for ~1000 km along the Alaskan coast and is the dominant circulation feature in Shelikof Strait and on the shelf along the Alaska Peninsula to Unimak Pass [Reed, 1987]. Shelikof Strait and its associated sea valley are <60 km wide and extend for ~450 km between the Alaska Peninsula and the Kodiak Island plateau (Figure 1). The sea valley forms a natural guide for circulation, connecting the inner shelf to the continental slope. In the confined areas of Shelikof Strait, current speeds (transport) can be appreciable, reaching values of ~100 cm s (3 × 10 m s) for brief periods (days) in winter [Schumacher et al., 1989]. Westward winds generally confine the freshwater discharge from the mountainous coastal regime to the nearshore. The wind can generate rapid fluctuations in the transport of the ACC in excess of 106 m s over the course of a day [Schumacher et al., 1989].

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Figure 1. The study area in the western Gulf of Alaska. The location of the moorings at Wide Bay (21-25, 28, and 29) and Cape Kekurnoi (1-3) are indicated by circles. The inset shows regional circulation. Depths are in meters.

Fisheries Oceanography Coordinated Investigations (FOCI) conducts research on the influence of physical and biological factors on the early life history of walleye pollock (Theragra chalcogramma) in the northeastern Gulf of Alaska. Large concentrations of adult pollock aggregate each March in western Shelikof Strait (Figure 1). They spawn in early April, and by late April patches of larvae can usually be found southwest of the spawning area. Since eggs and larvae are mainly planktonic, transport to this location is largely determined by currents and diffusion. To explore the variability in currents, a three-dimensional, primitive equation, hydrodynamic model driven by winds and freshwater discharge has been tuned to this region [Hermann and Stabeno, this issue].

The purpose of this paper is to compare the simulations from the numerical model with observations. Since the transport of pollock eggs and larvae is most strongly influenced by currents in spring and summer, we focus on this time period. We begin with a comparison between eddies that have been observed in the Shelikof sea valley and those generated by the model. A detailed comparison of model simulations with observations from moored current meters (for 1989 and 1991) follows. Finally, we compare float trajectories generated by the model with those of drifting buoys deployed off Cape Kekurnoi.

 

The Model

The eddy-resolving circulation model which we applied to the Shelikof Strait region is the rigid-lid semispectral primitive equation model (SPEM) of Haidvogel et al. [1991], which employs a topography-following ("sigma") vertical coordinate system. The horizontal grid is formulated in curvilinear-orthogonal coordinates, with 257 × 97 horizontal grid points and nine vertical levels. The full model domain is ~1500 × 500 km, with grid spacing telescoped (gradually increased) near the southern, eastern, and western boundaries. In the central, near-coastal region of interest, the mean grid spacing is ~4 km. Details of the model's implementation in this region are given by Hermann and Stabeno [this issue].

The density structure for each model run was initiated using salinity fields obtained from conductivity-temperature-depth (CTD) surveys [Reed, 1984; Reed et al., 1987; Johnson et al., 1988]. For each year studied the model was spun up from a state of rest starting in January of that year using the appropriate winds and the freshwater discharge. By the end of March the model was fully evolved, with strong flow throughout the sea valley. Velocity and salinity (low-pass filtered) at each grid point were stored at daily intervals. In addition, model results were stored at hourly intervals at the location of the moorings. Trajectories of floats were generated from the daily stored results of the model runs. These floats were constrained to remain at 40 m depth in conformance with the depth of the drogues for the satellite-tracked buoys.

 

Data

The data fall into the following two categories: (1) observations which are compared with the model simulations and (2) the forcing functions for the model. The first category consists of records from moored current meters and the trajectories of satellite-tracked drifting buoys. The second category contains the time series for winds and freshwater runoff (buoyancy flux). In addition, data from hydrographic surveys from 1981 were used to initialize the model density field.

 

Current Meters

In the spring of 1989, seven taut-wire moorings with 41 current meters were deployed off Wide Bay (moorings 21-25, 28, and 29 in Figure 1). In the spring of 1991, three taut-wire moorings containing 12 current meters were deployed off Cape Kekurnoi (moorings 1-3 in Figure 1). The 1989 data set is discussed by Bograd et al. [1994] and the 1991 data set by Stabeno et al. [1995b]. All current meters were Aanderaa model RCM 4 or RCM 6. Current speed and direction, temperature, and conductivity were sampled at hourly intervals. The current meter data were low-pass filtered with a cosine-squared, tapered Lanczos filter (half amplitude 35 hours, half power 42 hours) and resampled at 6-hour intervals. (The same filter was applied to the currents generated by the model prior to output.) Estimates of transport were calculated from the current velocity components normal to each section, multiplied by estimates of cross-sectional area [Bograd et al., 1994; Stabeno et al., 1995b].

 

Satellite-Tracked Drifting Buoys

From 1985 to 1994, 51 satellite-tracked drifting buoys were deployed off Cape Kekurnoi. All buoys were drogued at ~40 m. During 1986-1988 and 1994, holey sock drogues were used, while between 1987 and 1993, tristar drogues were used. An average of ~10 satellite fixes were obtained daily, with a standard position error of ~0.2 km. The buoys deployed since 1989 had tilt switches, which indicated when the drogue was lost. In earlier years the loss of the drogue was determined from examination of the relationship between the wind and the buoy's trajectory [Stabeno and Reed, 1991]. Since these buoys showed both inertial and tidal currents, the data were first splined (using an Akima spline) and sampled at 1-hour intervals and then a 35-hour low-pass filter was applied so that the data would be comparable to the model simulations.

 

Wind Forcing

Although direct measurements of winds in the northern Gulf of Alaska are rare, geotriptic winds calculated from sea level pressure provide fair representation of winds in the region west of Kodiak Island [Macklin et al., 1993]. Surface winds were computed from 12-hourly atmospheric surface pressure supplied by Fleet Numerical Oceanographic Center. The geotriptic winds were rotated 15° counterclockwise, speeds were reduced by 30% from the geostrophic value, and the results interpolated to the model grid.

The geotriptic winds in Shelikof Strait proper must be modified, since ageostrophic (downgradient) winds are common here. The terrain-induced wind variations in Shelikof Strait have been documented with research aircraft [Lackman and Overland, 1989] and a special observing network [Macklin et al., 1993]; since these variations are large and persistent, they can have a significant local impact on the upper ocean. A simple algorithm was developed from these observations to approximate the winds in Shelikof Strait from the large-scale sea-level pressure field [Stabeno et al., 1995a]. For a prescribed range of geostrophic wind directions the surface winds are assumed to be channeled and enhanced within the strait.

 

Buoyancy Forcing

High precipitation rates along the coast of the northeast Pacific Ocean produce a large freshwater discharge (annual mean 23,000 m s), which enters the shelf waters through many streams and rivers. Acting as a line source of buoyancy at the coast, it provides the freshwater input for the ACC [Royer, 1982]. Freshwater discharge is maximum in the early fall, decreases through the winter, and generally reaches a minimum in the late winter or early spring. Time series for the 3 years discussed in this paper are shown in Figure 2. During the winter, runoff was greatest in 1987 and smallest in 1991. The runoff from May through October was similar during each of the 3 years.

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Figure 2. Time series of the monthly mean freshwater input for 1987, 1989, and 1991 (data from T. Royer, personal communication, 1994).

 

Comparison Between Observations and Model Simulations

Eddies

Eddies are an integral part of the flow field in the Shelikof sea valley and, apparently, enhance larval survival [Schumacher et al., 1993; Bograd et al., 1994]. Noting this, it is important that the model generate eddies at the same rate and size as observed in the data (at least in a statistical sense). Eddies are generated in Shelikof Strait, primarily as a result of baroclinic instabilities, which are common there [Bograd et al., 1994; Mysak et al., 1981]. The eddies in the Shelikof sea valley generally range in diameter from 20 to 45 km, with peak rotational speeds of ~30 cm s [Bograd et al., 1994], although larger eddies have been observed in satellite images and satellite-tracked drifting buoy trajectories. The eddies generated by the model were generally larger (~60 km) than those observed in the data and rotated more slowly (~20 cm s). The number of eddies generated in model simulations during each of 3 years was similar to the number observed in 1989, when a census of eddies was conducted (Table 1). Model simulations and observations showed the following similar characteristics: cyclonic eddies were generally observed between April and May and not during August and September; in contrast, anticyclonic eddies were evident throughout the observation period; and each year, anticyclonic eddies occurred more frequently than cyclonic eddies.

If your browser cannot view the following table correctly, click this link for a GIF image of Table 1
Table 1. Number of Cyclonic/Anticyclonic Eddies Observed in 1989 and in Three Model Simulations

Model
Observation
1989 1987 1989 1991

April 1/0 1/3 0/0 1/0
May 1/3 0/1 0/2 1/2
June 1/1 1/2 1/2 0/1
July 1/2 1/4 0/0 0/1
August 0/1 0/0 0/0 0/1
September 0/1 0/0 0/2 0/2
Total 4/8 3/10 1/6 2/7

The 1989 observations are from Bograd et al. [1994].

The somewhat larger eddy scale observed in the simulations may be due, in part, to how the freshwater is added to the model. As described by Hermann and Stabeno [this issue], the salinity field is freshened at the coast upstream (northeast) of Shelikof Strait to represent freshwater input along the Gulf of Alaska. The length of coastline along which this input is distributed is shorter in the model than in the true gulf, due to the limited spatial domain of the former. This may result in stronger cross-shelf salinity gradients in the model, leading to larger Rossby radii and hence larger diameters of eddies produced through baroclinic instability.

In the model, large eddies (both cyclonic and anticyclonic) were generated at the onset of a storm, when a pulse of freshwater (salinity <31.0 practical salinity units (psu)) was forced down the strait. The cross-strait salinity gradient doubled from ~0.3 to ~0.6 psu during such events. An anticyclonic eddy dominated the sea valley for 60 days during the 1989 model simulation (Figure 3). Although an eddy was not evident in the current meter records at that time, features of similar size have been observed in the sea valley. During 1994 a large, cyclonic eddy was evident off Wide Bay in a satellite-tracked drifting buoy trajectory (not shown). This eddy was similar in size (~60 km) and location to that observed in the 1989 model simulation. Large eddies have also been observed in sea surface temperature from advanced very high resolution radar. During May 1987 one existed west of Kodiak Island for >10 days, with speeds of 30 cm s-1 [Vastano et al., 1992].

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Figure 3. The wind stress at 57.5°N, 155°W and the daily velocity at selected depths from current meter measurements and the 1989 model simulation. Series were rotated to along isobath (220°T). The bold lines indicate when the large eddy discussed in the text was present in the simulation.

Most eddies translated through the sea valley in a matter of weeks. In 1990 an anticyclonic eddy of smaller diameter (~25 km) was observed ~50 km to the west of the Wide Bay moorings [Schumacher et al., 1993]. This eddy remained stationary for at least 16 days, the longest observation of a stationary eddy. This, of course, does not prove that other eddies have not remained locked in position for a longer period, but none has been observed. We suspect that the large eddy evident in the model simulations of 1989 was stationary for a longer period than typical of eddies in the sea valley.

The vertical structure of a typical anticyclonic eddy (Figure 4) from the 1991 model simulations at Wide Bay was compared to an eddy observed at the same location in 1989 [Bograd et al., 1994]. The deformation of the salinity field (which at these temperatures determines the density field) in both modeled and observed eddies was greatest in the upper 100 m, while the velocity signature in both was evident almost to the bottom. As is typically the case, the simulated eddy was larger and not as intense as the observed eddy.

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Figure 4. The (a) salinity (practical salinity units) and (b) velocity (centimeters per second) structure of an eddy observed in the sea valley near Wide Bay in 1989 (from Bograd et al. [1994]) and the (c) salinity (practical salinity units) and (d) velocity (centimeters per second) structure of an eddy near Wide Bay simulated by the model. Hatched regions indicate flow toward the northeast (up the sea valley).

 

Current Meter Observations

The large, anticyclonic eddy, spawned in Shelikof Strait during the 1989 model simulation, remained stationary from June 21 to August 6 off Wide Bay. As a result, the model simulation from 1989 was analyzed in two parts, April 27 to June 21, when the model reproduced the low-frequency variability evident in the observations; and after June, when the eddy dominated the currents (Figure 3). The signature of the model eddy is evident in the current time series, with steady northwestward flow at mooring 22 and southeastward flow at mooring 25. Near the edge of the sea valley (mooring 22) the flow was generally along the isobaths in both modeled and observed flow. Farther to the center of the sea valley, however, strong across-shelf flow existed which was not reproduced by the model. This was particularly evident in the measurements at mooring 28. Correlations between modeled and measured currents, both for the entire record length and for the noneddy period, were not significant at the 99% level.

The current velocity between April 27 and June 21 (when the model currents were not dominated by the large eddy) was used to calculate the mean flow normal to the section (Figure 5). There was marked agreement between the observed and modeled mean flow. In both the observations and model simulations the strongest flow was toward the southwest on each side of the sea valley, with weak flow near the middle (moorings 24-28). Although both observations and simulations show estuarine inflow at depth, the modeled flow was weaker. This is also evident in Figure 3. In general, the shear was weaker in the model simulations than observations. The current simulations also lacked the high-frequency variability evident in the observed current.

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Figure 5. Cross section of mean alongshore current (centimeters per second) observed off Wide Bay for the period April 27 through June 6, 1989, from (a) current meter measurements and (b) model simulation. Hatched regions indicate flow toward the northeast (up the sea valley). Mooring locations are indicated at the top of each panel.

For 1991 the model reproduced the currents forced by the strong winds of spring and fall better than events forced by the weaker winds of summer (Figure 6). As occurred in 1989, the flow near the edge of the sea valley was predominately along the isobaths in both the model simulations and observation. Strong cross-shelf flow occurred at the center of the strait in the observations (mooring 2), which was not well simulated by the model. Significant correlation at the 99% level between modeled and measured currents existed only at mooring 1.

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Figure 6. The wind stress at 57.5°N, 155°W and the daily velocity at selected locations from current meter measurements and the 1991 model simulation. Series were rotated to along isobath (220°T).

The mean along-sea valley flow for the period April 21-September 28, 1991 (Figure 7), revealed results similar to those for 1989. Once again, there was marked agreement in the general pattern and magnitude of flow generated by the model and measured by current meters. The flow was strongest along the peninsula (mooring 1), with inflow occurring on the Kodiak Island side (mooring 3) of the strait. Again, the shear was weaker in the model results than in the observations. The reduced shear may be due to excessive vertical mixing in the model required for numerical stability. A comparison of terms for the salt balance in Shelikof Strait suggests that vertical mixing is, on average, ~35% as large as the horizontal advection term; this may be unrealistically large at middepth. (As noted by Hermann and Stabeno [this issue], horizontal mixing is generally insignificant in this balance.)

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Figure 7. Cross section of the mean alongshore current (centimeters per second) observed off Cape Kekurnoi for the period April 8 through September 30, 1991, from (a) current meter measurements and (b) model simulation. Hatched regions indicate flow toward the northeast (up the sea valley). Mooring locations are indicated at the top.

 

Transport

Time series of transport from current meter records for 1989 and 1991 were compared with the modeled transport (Figure 8). The large eddy, which dominated the currents in 1989 in the model simulations, reduced transport. While the response of transport to strong wind events was evident in both the measured and the modeled transport for both years, the modeled transport was larger by a factor of 2 on several occasions. This was particularly evident in late May 1989 and September 1991 and, to a lesser extent, in September 1989. The mean transport during 1989 (0.5 × 10 m s) compared well with that simulated by the model (0.6 × 10 m s). For 1991, however, the modeled transport (1.0 × 10 m s) was larger than that observed (0.6 × 10 m s), primarily because the model overestimated transport in September. Correlation between the measured and modeled transport for 1989 was less (r = 0.45) than for 1991 (r = 0.60).

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Figure 8. Time series of transport (as measured by current meters and simulated by the model) through (a) the section off Wide Bay (1989) and (b) through the section off Cape Kekurnoi (1991).

The spectra of the modeled and measured transport (Figure 9) compare well at frequencies below 0.35 cpd. At higher frequencies the model transport had significantly less energy than the measured transport. For both years the modeled and measured transport were coherent at the lowest-frequency band (Figure 9). There was a lack of coherence at the next frequency band and a return of significance in the weather band. This pattern of coherence is similar to that observed between measured transport and winds [Stabeno et al., 1995b]. The coherence between the modeled transport and alongshore wind also shows a lack of coherence at frequencies of ~0.09 cpd, with high coherences at frequencies above and below.

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Figure 9. Spectra of the modeled and measured transport for (a) 1989 and (b) 1991. Frequencies at which the coherence between measured and modeled transport was above 0.44 (95% significance level) are indicated with solid circles.

While the individual current time series are generally not correlated with the alongshore winds (with the exception of mooring 1 from 1991), the transports are. The lack of correlation between winds and individual current records was due both to occurrence of eddies and to the variability in the location of the high-speed core of the ACC. The significant correlations at mooring 1 were due to the fact that the ACC primarily flows along the peninsula, and eddies tend to quickly cross this region. The wind series used for comparison was the same as that which forced the model. Thus we expected the correlations between modeled transport and alongshore wind (r = 0.66, 0.70) to be higher than between observed transport and alongshore wind (r = 0.47, 0.50) during 1989 and 1991, respectively. The correlations did not differ significantly between the 1989 and 1991 comparisons.

 

EOF Analysis

While empirical orthogonal function (EOF) analysis is often used to obtain modes of motion that are related to dynamical modes, here we use this technique to compare the principal modes of variability in the currents simulated by the model with those measured by the current meters. During 1989 the horizontal structure of the currents generated by the model were markedly different from that observed because of the eddy which dominated model simulation that year. Limiting our analysis to just the noneddy period results in time series which are too short to significantly resolve the structure.

Noting this, we concentrate on the 1991 comparison (Figure 10). The first complex EOF mode accounted for 50% (66%) of the variance in the measured (modeled) currents. Most of the energy in both the modeled and observed current is concentrated along the Alaska Peninsula. The weaker vertical shear in the model resulted in the reduced shear in the EOF of the modeled current compared with measured; otherwise, the two patterns are markedly similar. Furthermore, the time series of these EOFs were significantly correlated (r = 0.58). The second-mode EOF accounted for ~20% of variance in both the modeled and measured time series, but the time series were not significantly correlated nor were the horizontal structures similar.

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Figure 10. The horizontal structure for percent variance explained by the first empirical orthogonal function mode at each current meter location for (a) observed and (b) modeled currents during 1991.

 

Drifting Buoy Trajectories

There was a marked similarity between the float trajectories generated by the model for 1987 and the trajectories of satellite-tracked drifting buoys for that year (Figure 11). While the trajectories have similar mean paths, their variability is not correlated. This is largely due to the occurrence of eddies and their effect on a trajectory. An eddy is clearly evident in the trajectories of the floats from the model in Figures 11b and 11d. This eddy delayed the exit of these floats from the sea valley for ~50 days. For the two floats that were not entrained in the eddy (Figures 11a and 11c) the transit time through the sea valley was very similar to that of the satellite-tracked buoys (<40 days). A general tendency of buoys was similar to that of model floats; that is, buoys deployed (or floats seeded into the model) nearest the Alaska Peninsula tend to continue along the coast (not shown), while those started toward the middle of the strait and nearer Kodiak Island tend to follow the sea valley.

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Figure 11. Trajectories of four buoys deployed in 1987 (thin solid lines) compared with buoys seeded at the same location and time into the model simulations (thick solid lines). Solid circles indicate every 10 days.

The trajectories from 51 satellite-tracked buoys were used to derive a mean velocity field at 40 m (Figure 12a), following Stabeno and Reed [1991]. While most buoys were from 1987, every year but 1989 was represented (Table 2). The data come predominantly from April-October. The measured drift velocities were averaged in 25 × 25 km bins and interpolated to the velocity field shown in Figure 12a. The mean (April-September) horizontal velocity field at 40 m from the model for each of the 3 years already discussed is also shown (Figures 12b-12d). There is good agreement between the current patterns derived from the satellite-tracked drifting buoys and the model, especially for 1987, although there is significant variability between years in the model results. The simulations for 1989 had the weakest mean flow, while the simulations for 1987 and 1991 had stronger flow, similar to the drifter-derived pattern.

If your browser cannot view the following table correctly, click this link for a GIF image of Table 2
Table 2. Number of Buoys Used in the Determination of the Mean Velocity Field (Figure 12a)

Year Number of Buoys Number of Days

1986 7 326
1987 16 1033
1988 1 40
1989 0 0
1990 3 211
1991 6 116
1992 6 236
1993 6 195
1994 6 388

The total number of days indicates how long the buoy remained within the area where the flow field was determined.

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Figure 12. Maps of horizontal currents at 40 m (a) generated from the trajectories of 51 satellite-tracked drifting buoys and simulated by the model for (b) 1987, (c) 1989, and (d) 1991.

The modeled and observed coastal flow fields were all dominated by the ACC which flows to the southwest through Shelikof sea valley (~25 cm s). The mean velocity field showed a strong return flow onto the shelf south of the Semidi Islands, which flowed offshore at the Shumagin Islands. This pattern was also evident in the 1987 computer simulation and, to a lesser extent, in 1989 and 1991. The flow (~10 cm s) which occurred along the peninsula, however, was largely absent from each of the model simulations. This is likely caused by the strong tendency of the currents in the model to follow the bathymetry and thus flow down the sea valley. Another source of this discrepancy is the smoothed bathymetry used by the model; narrow areas of >40 m depth in the near-coastal region were often excluded. Since 1989 had no satellite-tracked drifting buoys, the lack of similarity in the strength of the currents between the observed and modeled flow from 1989 is not surprising. The Alaskan Stream in the model was wider and weaker than observed in the data because the model was limited to a maximum depth of 500 m.

Since eddies were not produced at the same time in the model as in the sea valley, correlations between records that included eddy variability are poor. Once the data are integrated in time or space (thus removing the effect of the randomly spaced eddies), the comparisons are very good. Correlations between individual observations and model simulations can hopefully be improved by assimilation of current meter data. This particular problem will be explored in the future.

 

Acknowledgments. We thank T. Royer for runoff data from the Alaskan coast. Simulations were performed on a Cray Y-MP with generous support from the Arctic Region Supercomputing Center, Fairbanks, Alaska. This is contribution FOCI-0221 to Fisheries Oceanography Coordinated Investigations, PMEL contribution 1612, and contribution 265 from the Joint Institute for the Study of the Atmosphere and Oceans under cooperative agreement NP90RAH00073.

 

References

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Haidvogel, D. B., J. L. Wilkin, and R. Young, A semi-spectral primitive equation ocean circulation model using vertical sigma and orthogonal curvilinear horizontal coordinates, J. Comput. Phys., 94, 151-185, 1991.

Hermann, A. J., and P. J. Stabeno, An eddy-resolving model of circulation on the western Gulf of Alaska shelf, 1, Model development and sensitivity analyses, J. Geophys. Res., this issue.

Johnson, W. R., T. C. Royer, and J. L. Luick, On the seasonal variability of the Alaska Coastal Current, J. Geophys. Res., 93, 12,423-12,437, 1988.

Lackman, G. M., and J. E. Overland, Atmospheric structure and momentum balance during a gap-wind event in Shelikof Strait, Alaska, Mon. Weather Rev., 117, 1817-1833, 1989.

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Mysak, L., R. D. Muench, and J. D. Schumacher, Baroclinic instability in a downstream varying channel: Shelikof Strait, Alaska, J. Phys. Oceanogr., 11, 950-969, 1981.

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Reed, R. K., Salinity characteristics and flow of the Alaska Coastal Current, Cont. Shelf Res., 1, 573-576, 1987.

Reed, R. K., J. D. Schumacher, and L. S. Incze, Circulation in Shelikof Strait, Alaska, J. Phys. Oceanogr., 17, 1546-1556, 1987.

Royer, T. C., Coastal freshwater discharge in the northeast Pacific, J. Geophys. Res., 87, 2017-2021, 1982.

Schumacher, J. D., and R. K. Reed, Coastal flow in the northwest Gulf of Alaska: The Kenai Current, J. Geophys. Res., 85, 6680-6688, 1980.

Schumacher, J. D., P. J. Stabeno, and A. T. Roach, Volume transport in the Alaska Coastal Current, Cont. Shelf Res., 9, 1071-1089, 1989.

Schumacher, J. D., P. J. Stabeno, and S. J. Bograd, Characteristics of an eddy over a continental shelf: Shelikof Strait, Alaska, J. Geophys. Res., 98, 8395-8404, 1993.

Stabeno, P. J., and R. K. Reed, Recent Lagrangian measurements along the Alaskan Stream, Deep Sea Res., 38, 289-296, 1991.

Stabeno, P. J., A. J. Hermann, N. A. Bond, and S. J. Bograd, Modeling the impact of climate variability on the advection of larval walleye pollock (Theragra chalcogramma) in the Gulf of Alaska, in Climate Change and Northern Fish Populations, edited by R. J. Beamish, Can. Spec. Publ. Fish. Aqu. Sci., 121, 719-727, 1995a.

Stabeno, P. J., R. K. Reed, and J. D. Schumacher, The Alaska Coastal Current: Continuity of transport and forcing, J. Geophys. Res., 100, 2477-2485, 1995b.

Vastano, A. C., L. S. Incze, and J. D. Schumacher, Observations and analysis of fishery processes: Larval pollock at Shelikof Strait, Alaska, Fish. Oceanogr., 1, 20-30, 1992.


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