A Coupled Global/Regional Circulation Model for Ecosystem Studies in the Coastal Gulf of Alaska
A. J. Hermann1, D. B. Haidvogel2, E. L. Dobbins1,
P. J. Stabeno3 and P. S. Rand4
1Joint Institute for the Study of Atmosphere and Ocean (JISAO)
University of Washington
Seattle, WA 98195
2Institute of Marine and Coastal Sciences
Rutgers University
New Brunswick, New Jersey 08903
3Pacific Marine Environmental Laboratory (PMEL)
National Oceanic and Atmospheric Administration (NOAA)
Seattle, WA 98115
4Department of Zoology
North Carolina State University
Raleigh, NC 27695
For submission to: Progress in Oceanography
January 2000
Contribution No. 2174 from NOAA/Pacific Marine Environmental Laboratory
ABSTRACT
To study the impact of interannual-to-decadal
changes in circulation and hydrography on lower trophic level dynamics
in the Coastal Gulf of Alaska (CGOA), we are developing a suite of nested
physical and biological models as part of the West Coast U.S. GLOBEC program.
Components of the multi-scale system include a variable-resolution, global
circulation model; a higher-resolution, regional circulation model; a lower
trophic level (NPZ) model; and an individual-based salmon model. Here we
describe the attributes and coupled behavior of the first two of these
components.
The global circulation model is a version
of the Spectral Element Ocean Model implemented in layered, primitive equation
form on an unstructured grid, and driven by global winds. The regional
physical model consists of the S-Coordinate Rutgers University Model configured
with approximately 22 km resolution in the CGOA and driven by runoff, heat
fluxes and wind stresses appropriate to years 1976, 1995, 1996 and 1997.
The coupled models develop appropriate boundary currents (the Alaskan Stream
and the Alaska Coastal Current), and also spin up large (~200km) eddy features
which appear to play a significant role in cross-shelf exchange.
Model-generated seasonal patterns and eddy
structures are consistent with recent and historical data (hydrographic,
drifter track, SSH, and SST). As part of our model validation for GLOBEC,
we explore: 1) interannual differences in the broad regional circulation
and temperature; 2) Eulerian and Lagrangian aspects of a large eddy feature
near Sitka, Alaska; and 3) the impacts produced by forcing the regional
model with barotropic data from the global model.
1. Background
1.1. Goals of this project
A core hypothesis of the U.S. GLOBEC Northeast
Pacific program is that interannual to interdecadal variability in the
circulation and hydrography of the Gulf of Alaska drives changes in productivity
of zooplankton in the coastal zone, with consequent effects on the feeding
success of salmonids and other species in the Gulf (U.S. GLOBEC, 1996).
This hypothesis is partly based on strong evidence that a major shift in
both the physical and biological character of the Gulf of Alaska occurred
in 1976-1977 (Trenberth, 1990; Brodeur and Ware, 1992; Trenberth and Hurrel,
1994; Brodeur and Ware 1995; Brodeur et al., 1996). Trenberth (1990) documented
a deepening and eastward shift of the Aleutian Low as part of that climate
shift. However, a recent analysis by Lagerloef (1995) suggests that this
deepening was in fact accompanied by weakened wind-driven cyclonic circulation
in the Gulf. Polovina et al. (1995) showed that mixed layer temperatures
rose in the Gulf after the climate shift, while the mixed layer shoaled.
Brodeur and Ware (1992) demonstrated enhanced zooplankton levels after
the shift, especially towards the coastal perimeter of the Gulf, which
they attributed in part to greater Ekman drift of zooplankton out of the
central Northern Pacific.
To address these issues for the CGOA, we
have been developing with our biological colleagues a set of linked circulation
models, coupled with a lower trophic level Nutrients-Phytoplankton-Zooplankton
(NPZ) biological model, and an individual-based model (IBM) of salmon.
Specific issues to be addressed by this set of models include the relative
importance of surface Ekman flux, flows through submarine canyons, and
mesoscale eddies on cross-shelf exchange, and the subsequent impacts of
that exchange on plankton and fish (both through resupply of nutrients
and transport of the organisms themselves).
As part of this larger effort for GLOBEC,
we have thus far developed both global and regional circulation models,
bathymetry and forcing datasets for each, and a method for passing information
from the global to the regional model. Initial runs have yielded prominent
spatial, seasonal and interannual differences. Here, our goals are: a)
to describe the coupled global/regional physical modeling system; b) to
assess the primary features of the physical circulation generated by the
coupled physical models; c) to describe eddy dynamics of the regional model
in the vicinity of the widely reported eddy near Sitka AK (the "Sitka Eddy"
first reported by Tabata [1982]); and d) to use Lagrangian tracking as
a zero-order method to infer how such eddy-scale variability and Ekman
flux could affect plankton and salmon dynamics in the CGOA.
1.2. Overview of circulation in the GOA
We begin by reviewing present knowledge about the mean circulation and biology of lower trophic levels in the Gulf of Alaska, and their variability. The Gulf of Alaska contains two major current systems: the Alaskan Current (AC)- Alaskan Stream (AS) and the Alaska Coastal Current (ACC) (Fig. 1). The AS is the intensified northern boundary of the AC; both are part of the subarctic gyre forced by cyclonic winds in the northeastern Pacific. Reed and Schumacher (1986) summarized knowledge of the AC-AS and ACC; significant new data have been reported since their review.
Fig. 1. Overview of circulation in the
Gulf of Alaska.
The subarctic gyre of the Northeast Pacific
is much broader in the east than in the western part of the GOA, where
it forms the narrow, swift AS (Reed, 1984). This juxtaposition of eastern
and western boundary currents is unique. The AS is constrained by a steep
continental rise which parallels the Aleutian Island chain. It is generally
steady on seasonal time scales, but varies interannually (Reed, 1984; Musgrave
et al., 1992; Lagerloef, 1995). Chelton and Davis (1982) first suggested
that the transport in the Alaska and California Current systems fluctuated
out of phase on interannual time scales, both being fed by the West Wind
Drift. Kelly et al. (1993) found such interannual fluctuations in altimeter
data.
The annual mean flow of the AS is approximately
10 Sv above 500 m depth, and between 15-30 Sv integrated to the bottom,
with significant interannual variability (Reed, 1984); this annual mean
conforms to forcing by the annual mean integrated wind stress curl of the
far northern Pacific (Musgrave et al., 1992). In AVHRR imagery, the AS
typically shows up as a warm band of SST along the shelf break in the northern
Gulf (Royer 1983). Lagerloef's (1995) analysis of wind climatology indicates
a net southward Ekman transport of 1 Sv from the Gulf, and divergence ~300
km offshore at the head of the Gulf corresponding to an upwelling rate
of 3x10-6 m/s. Interannual variability of sea surface height
in the Gulf has been observed using altimeter data (Bhaskaran et al., 1993;
Matthews et al., 1992; Strub and James, 2000a,b).
The intermittently formed Sitka eddy centered
off Sitka, Alaska (Tabata, 1982), and meanders of the Alaskan Stream in
the central and western Gulf (Musgrave et al., 1992; Reed and Stabeno,
1993; Stabeno and Reed, 1989; Thomson and Gower, 1998) are prominent mesoscale
features with scales of ~200 km. These features have been measured with
sea surface height (TOPEX), sea surface temperature (AVHRR), and hydrographic
(T, S, O2) data. TOPEX data in particular has indicated lifespans of months
to years (Crawford and Whitney, 1999). These large eddies typically drift
at < 2 cm/s, are predominantly anticyclonic, are more commonly observed
in spring. Modeling studies have suggested that such eddies near the shelf
break are intensified by ENSO warm events (Melsom et al. 1999).
Royer (1989) found decadal variation in
spatially averaged SST data for the Gulf, as did Polovina et al. (1995),
who noted shoaling of mixed layer depths during 1976-1988. Lagerloef (1995),
using EOF (empirical orthogonal function) analysis of XBT and CTD data
spanning 1968-1990, found a consistent pattern for interdecadal variations
in the Gulf. His time series for the first mode dynamic height EOF (referenced
to 500db) exhibited a striking correlation with both: 1) the North Pacific
anomaly, defined by Trenberth and Hurrel (1994) as an index of the strength
and position of the Aleutian Low, and 2) a time series of observed SST
anomalies for the Gulf. Evidently, when the Aleutian Low is strong (as
in the period 1976-1989), the AC-AS circulation is weaker and the spatial
mean SST of the Gulf rises. The weakened circulation appeared to result
from anticyclonic anomalies in the wind stress curl pattern over the Gulf
during periods of intense Aleutian Low. Concurrently in the central Pacific,
mixed layer depth increased and SST declined (Polovina et al., 1995). During
the early 1970's the Aleutian Low was weak, the anticyclonic circulation
in the Gulf more intense and SST depressed below the long term mean value.
Shorter-term fluctuations associated with El Nino also exhibit this spatial
pattern (Lagerloef, pers. comm.).
The ACC is driven by a widely distributed
coastal source of freshwater and downwelling favorable winds (Royer, 1981;
Schumacher et al., 1990). Continuity of this current in the northern and
western Gulf has been established (Stabeno et al., 1995a). Freshwater input
is greatest in October and smallest in March (Royer, 1982), while downwelling-favorable
winds peak in January for the northern Gulf (Royer, 1983; Wilson and Overland,
1986). Estimated runoff is well correlated with measured baroclinic transport
in the northern Gulf (Royer, 1983); the transport is ~30 times larger than
the runoff value. Salinity determines the density field for much of the
year, but a seasonal thermocline forms in the summer (Royer, 1983; Stabeno
et al., 1995a).
Significant bifurcation of the ACC occurs
at several locations along the coast, with branches joining the AS. The
first bifurcation is directly west of Kayak Island, near the eastern edge
of Prince William Sound (Royer et al., 1979). The second is at Kennedy-Stevenson
entrances east of Shelikof Strait, where ~25% of the transport flows along
the south side of Kodiak Island, eventually joining with the AS. The third
is at the western exit of Shelikof Strait, where -25% joins the AS. Finally,
near the Shumagin Islands ~50% of the remaining ACC joins the AS (Stabeno
et al., 1995a; Stabeno and Reed, 1989; Stabeno, unpublished data).
As with the AC-AS system, there are significant
differences in the character of the ACC between the eastern and western
Gulf. The shelf is much broader in the northern and western Gulf than further
east, while bathymetric irregularities (banks and canyons) are found in
all areas. Alongshore wind forcing is considerably weaker in the eastern
Gulf (Wilson and Overland, 1986), with strongest downwelling-favorable
winds in the north and west. Flow of the ACC is also weaker in the eastern
GOA (Reed et al., 1981); presumably this is due mainly to the weaker local
downwelling. It has been suggested that the baroclinic structure of the
ACC at this upstream location is too weak to support baroclinic instability
(Swaters and Mysak, 1985), which is prevalent in parts of the western Gulf
(Mysak et al., 1981).
Interannual variability of the ACC has
been documented by Stabeno et al. (1995a), and some decadal variability
is evident in the long-term hydrographic series of Royer at approximately
150 degrees W (the GAK line). An 18.6 year signal was discovered in the
GAK temperature series, which Royer (1993) hypothesized might be due to
modulation by tidal forcing at that frequency. Positive temperature anomalies
were also recorded at depth at the GAK line, 6-9 months after each of two
El Nino events. In addition, Royer (pers. comm.) has noted decadal trends
in his CGOA runoff time series, which could affect trends in the strength
of the ACC and mixed layer depths of the Gulf.
There has been considerably more study
of circulation in the Gulf west of 150 degrees W, largely as a result of
the ongoing Fisheries Oceanography Coordinated Investigations (FOCI) program
(Schumacher and Kendall, 1995) in that region. Moored current meter records,
in conjunction with geostrophic calculations from CTD casts, indicate that
the mean flux of the ACC through Shelikof Strait in the spring is ~0.6
x 106 m3/s (Reed and Schumacher, 1989; Reed and Bograd,
1995). However, data from cross-strait arrays of current meters convey
intense variability, from weakly reversed transport to fluxes as strong
as 3 x 106 m3/s, on a time scale of days (Schumacher
et al., 1990). A sea valley connects deep waters of the Strait with the
open Gulf (see Fig. 1). An estuarine type circulation pattern is observed
in the sea valley, with deep water entering below 150 m, and southwestward
surface outflow on the northwestern side (Schumacher et al., 1990).
Meanders and eddies are common features
of the sea valley, resulting from baroclinic instability of the mean flow
through the Strait (Mysak et al., 1981). Remotely-sensed sea surface temperature
data (AVHRR), in conjunction with drifter tracks and CTD surveys, have
clearly revealed the presence of eddies with approximately 25 km radius
and lifetimes of several weeks (Vastano et al. 1992; Schumacher et al.,
1993). These eddies extend below 100 m depth (Schumacher et al., 1993;
Bograd et al, 1994), and translate at speeds much slower than the mean
currents of the valley (Schumacher et al., 1993). A persistent eddy has
also been revealed by hydrographic and drifter data just west of Kayak
Island (Royer et al., 1979). It is presently unknown what role the nearby
Copper River outflow may play in the maintenance of this eddy, although
models of coastal buoyancy outflows (Chao and Boicourt, 1986; Kourafalou
et al., 1996) suggest a possible link.
Tidal currents are strongest in the vicinity
of Kodiak Island, and especially strong in Cook Inlet, where tidal currents
in excess of 100 cm s-1 have been observed. Tidal models of Isaji and Spaulding
(1986) and Liu and Leendertse (1986; 1990) show good agreement with these
observations. Both models and the data of Schumacher and Reed (1980) indicate
strong tides and resultant tidal mixing on Portlock Bank, just east of
Kodiak Island.
2. Methods
2.1. Overview of CGOA models
Past physical modeling efforts for the
CGOA relevant to the present study include: global eddy-resolving models
which include the Gulf (Semtner and Chervin, 1992; Fu and Smith, 1996),
North Pacific models which include the Gulf (Cummins and Mysak, 1988; Ingraham
and Miyahara, 1988; Cummins, 1989; Hsieh and Lee, 1989; Heim et al., 1992;
Hurlburt et al., 1992; Lee et al., 1992; Cummins and Freeland, 1993; Miller
et al., 1994; Hurlburt et al., 1996), regional models of portions of the
Gulf (Isaji and Spaulding, 1986; Liu and Leendertse, 1990; Hannah et al.,
1991; Foreman et al., 1992; Waiters and Foreman, 1992; Foreman et a1.,
1993) and very local models of specific estuaries and embayments. Both
Cummins (1989) and Lee et al. (1992) noted the importance of bottom topography
in limiting the variability and setting the vertical structure of flows
in the AC-AS system.
As components of the Shelikof Strait FOCI
program, Stabeno et al. (1995b) and Hermann and Stabeno (1996) have used
a primitive equation model in topography-following coordinates (the S-coordinate
Primitive Equation Model [SPEM] of Haidvogel et al., 1991) to explore interannual
variability in the circulation between Kodiak Island and the Shumagin Islands
in the northern and western GOA. The model is driven with FNOC winds and
the runoff series of Royer (1982 and personal communication). Stabeno and
Hermann (1996) demonstrate how the model compares favorably with observed
currents near Shelikof Strait.
Large-scale wind forcing is obviously significant
for the AC-AS, whereas for the ACC both wind and nearshore buoyancy forcing
play a crucial role. Biologically relevant physics near the coast include
the freshwater input, baroclinic instability at scales of tens of kilometers,
tidal mixing fronts anchored to small-scale topographic features, and frontal
activity near the shelf break due to the generation of internal tides (Huthnance,
1995). Quasigeostrophic and layer models cannot realistically incorporate
the relevant coastal physics (runoff and tides), while full primitive equation
level models are very expensive to run at very high resolution on basin
scales. Simple 1-1/2 layer basin/coastal models allow high resolution and
capture some wave dynamics, but exclude baroclinic instability and tidal
mixing effects. The primitive equation model of Hermann and Stabeno (1996)
for Shelikof Strait and downstream includes the baroclinic instability
physics, but is limited in spatial coverage.
To satisfy the multiple aims and long time
scales of GLOBEC, we have been developing a set of coupled global and regional
models, with finest resolution in the CGOA. A suitable regional coastal
model needs to have sufficient resolution to resolve at least some of the
baroclinic instabilities of the flow. Vertical resolution needs to be sufficient
to allow decoupling of the flows from topography under stratified conditions
and development of appropriate shears when the flow is baroclinically unstable,
and at least partially resolve boundary layers at the top and bottom of
the water column, which meet in the shallow regions. Ideally the regional
model should be informed at its boundaries with circulation and scalar
fields appropriate to specific days and years. In the following sections
we describe the global and regional models presently used to begin to achieve
these intricate modeling objectives, and how global model output can be
used to constrain the regional model simulations.
2.2. The Global Model
A large-scale context for our regional
studies is provided by simulations with the Spectral Element Ocean Model
(SEOM; Haidvogel and Beckmann, 1999). SEOM has been developed for the purpose
of high-resolution basin-scale modeling on unstructured global grids (Iskandarani
et al., 1994). The governing equations are the 3-D, Reynolds-averaged Navier-Stokes
equations with Boussinesq and hydrostatic assumptions. Lateral subgridscale
mixing of momentum is parameterized using the shear- and mesh-size-dependent
formulation of Smagorinsky (1963), which has proven to be highly effective
on these horizontally heterogeneous grids. Vertical transfer of momentum
is represented with weak (linear) interfacial drag and (nonlinear) sress
laws. The resulting class of large-scale circulation models has several
significant virtues over those using more traditional approaches, including
complete geometric flexibility, regionally selective horizontal resolution,
and the ability to avoid open boundary conditions by use of global grid
refinement.
The spectral element circulation model
has now been applied in its reduced gravity form to a variety of test problems
and global oceanic/atmospheric applications. When applied to a now-standard
suite of shallow water test problems on the sphere, the SEOM model is shown
to be highly competitive with other numerical models, including those based
on spherical harmonic methods (Taylor et al., 1996). Oceanic applications
on global, non-uniform grids show that these favorable properties are maintained
in the presence of continental geometry and highly unstructured elemental
meshes (Haidvogel et al., 1996).
Here, for economy, SEOM has been implemented on a global grid in layered form with a total of five isopycnal layers (Fig. 2). Following Hurlburt el al. (1996), outcropping of the layers is avoided by mass sharing between layers as a minimum "entrainment thickness", here taken to be 40 meters, is reached. Table 1 gives the relevant parameters (resting layer thicknesses and reduced gravities) used in the global simulation. A significant limitation of the non-outcropping layered model is that topographic variations must be contained within the lowermost layer. We have done so here by clipping topography (obtained from ETOP05) at 200 meters (minimum) and 5000 meters (maximum), and then multiplying the resulting topographic excursions above 5000 meters by 0.85. Some of the effects of this topographic shrinkage are noted below.
Fig. 2. Layout of quadrilateral elements
for our layered implementation of the Spectral Element Ocean Model (SEOM).
Structure within each quadrilateral is represented with a polynomial basis
set of order eight. The resulting average "grid spacing" is approximately
25 km around the periphery of the North Pacific Basin, and increases to
about 100 km elsewhere.
Table 1. Mean interface depths (m) and reduced gravity at interfaces (m/s2) for the layered implementation of the Spectral Element Ocean Model.
Interface Depth, m | Gravity at interface, m/s2 |
0 | 9.810 |
135 | 0.020 |
320 | 0.009 |
550 | 0.004 |
800 | 0.002 |
As a first test of behavior, the global
layered model has been forced with a repeating cycle of NCEP winds, corresponding
to the period of NCSAT wind availability (August 1996 through July 1997).
A comparable simulation using NSCAT winds has also been prepared, as a
basis for a future sensitivity study. No explicit thermodynamic forcing
is included; therefore, the resulting simulations can at most represent
the wind-driven component of the large-scale, low-frequency circulation.
The SEOM model is highly scalable on parallel computing platforms (Curchitser
et al., 1998). The simulations reported below have been obtained on a Beowulf-type
cluster of Sun Ultra-5 workstations maintained at the Institute of Marine
and Coastal Sciences, Rutgers University. On this system, a year's simulation
requires approximately six cpu days when run on 12 processors.
2.3. The Regional Model
To capture regional circulation in the
CGOA, we employed the S-Coordinate Rutgers University model (SCRUM) of
Song and Haidvogel (1994). This free surface, primitive equation model
uses curvilinear-orthogonal coordinates in the horizontal, while the stretched,
bottom-following "s-coordinate" allows for flexible spacing of vertical
grid points. The latter feature is especially useful in resolving boundary
layers at the top of the water column (important for wind mixing) and near
the bottom (important for tidal mixing). Initial experiments with a coast-following
versus rectilinear coordinate system established the latter as the more
economical choice for the highly curved CGOA coastline. Ultimately we implemented
the model on a rectilinear telescoped grid, oriented at 38 degrees to true
north. In SCRUM, land areas are "masked out" after the calculation of each
timestep, but still entail some computational overhead. Our rotated grid
is designed to efficiently cover coastal and basin areas of the GOA, while
minimizing coverage of land areas to enhance computational efficiency.
A telescoped horizontal grid was employed to further reduce computational overhead associated with horizontal boundary conditions. The grid has 145 by 113 horizontal gridpoints with 17 telescoped gridpoints on the southern and western boundaries (Fig. 3). The finely resolved area of the model domain reaches from the northeast corner to Queen Charlotte Island in the south and Unimak Pass in the west. The telescoped region continues to the south end of Vancouver Island, and to Amukta Pass in the west. Grid resolution varies from 22 km in the finely resolved area, to 200 km near the western and southern walls. As described in a subsequent section, the telescoped regions here serve primarily to recirculate flows into and out of the area of interest.
Fig. 3. Layout of the telescoped rectilinear
grid for our regional implementation of the S-Coordinate Rutgers University
Model (SCRUM).
To allow proper resolution of top and bottom
boundary layers, we employed 20 vertical levels. We utilized the s-coordinate
feature of SCRUM to achieve quasi-uniform spacing near the surface, with
limits of 2.5 m in the shallowest areas and 3.6 m in the deepest areas.
This quasi-uniform spacing will be of especial benefit for planned coupling
with the biological models. Our CGOA implementation of SCRUM is forced
by winds, coastal runoff and atmospheric heat flux. Details of the forcing,
bathymetry, and boundary conditions are given in the following sections.
SCRUM is written in highly vectorized code, and most of the simulations
were obtained on vector architectures (CRAY J932) at the Arctic Region
Supercomputing Center. However, recent simulations have been obtained on
an equally fast, single-processor workstation at PMEL. On the CRAY platform
a year's simulation requires approximately 7 CPU days; on the local workstation,
5 CPU days are required.
2.3.1. Bathymetry
Model bathymetry was interpolated from
a specially developed 5-minute bathymetric map of the CGOA, based on ETOP05
and other sources. While ETOPO5 has the advantage of broad coverage, it
is well known to be inaccurate in many coastal areas. More detailed and
accurate bathymetric data used to improve ETOP05 was obtained from two
different sources: 1) Nearshore data from the National Ocean Service (NOS)
Hydrographic Data Base, error checked and gridded to 30 seconds by National
Geophysical Data Center (NGDC) and distributed as the TerrainBase data
collection. These data are focused on specific coastal areas such as Cook
Inlet. 2) Offshore data from Smith and Sandwell (1997), who collected and
verified coastline and marine ship track data from many sources, and distributed
that data as part of their 2 minute measured and estimated digital topographic
map. Though their estimated bathymetry (based partly on gravity anomalies)
contains too much noise to be useful on the continental shelf, the measured
bathymetry was easily extracted and used to improve ETOPO5 values offshore.
A complete collection of descriptions of available bathymetry and topographic
data sets has been compiled by Robert A. Kamphaus (http://newport.pmel.noaa.gov/~kamphaus/time/data.html).
Data from these two detailed sources were
combined and interpolated to a 5-minute grid using Global Mapping Tools
(GMT). To reduce computation effort, the interpolations were done for 10
deg. by 10 deg. areas that overlap by .25 deg. The interpolated grid points
match those of ETOPO5 so that when they were combined, ETOPO5 seamlessly
supplies data in areas where the detailed bathymetry data set is lacking.
The final data set is particularly accurate in areas of high data resolution, such as along the shelf break. It constitutes a major improvement over ETOPO5, especially in shallow shelf areas such as the Trinity Banks southwest of Kodiak Island. After interpolation to the SCRUM grid, bathymetry was cropped to 50 m minimum and 4000 m maximum, and filtered with six passes of a Shapiro filter, for numerical stability of the simulation. . The result is shown in Fig. 4. Even after filtering, the result is considerably more accurate than any bathymetry obtainable with ETOP05 alone.
Fig. 4. Smoothed bathymetry used for the
regional model simulations. In this and subsequent regional model results
figures, the axes are aligned with those of the model (that is, rotated
38 degrees relative to true north), and units are model gridpoints in the
two coordinate directions ("xi" and "eta"). Distance between successive
gridpoints is approximately 22 km.
2.3.2. Heat Flux and Wind Stress
Both wind and heat flux contribute substantially
to the near-surface dynamics of the CGOA. Suitable values of wind and heat
flux in specific years were obtained from the NCEP/NCAR Global Reanalysis
Project. NCEP products include a global data set of atmospheric variables,
obtained by combining a global spectral model with historical data. Their
model has been run for the years 1958-present, and the output is available
online. Resolution of these data is roughly 2 degrees. Temporal resolution
is 6 hours, but we have chosen to use daily averages as input to our regional
circulation model.
Daily average NCEP/NCAR values for latent
and sensible heat net flux, and net longwave and shortwave radiation were
summed to provide total heat flux from the ocean. Daily average U-wind
and V-wind at 10m height above the ocean surface were converted to wind
stress using the simple formula:
t = ra*
Cd * U10 * |U10|
where t
is the wind stress in N/m2 , U10 is the vector of wind speed
in m/s, ra
is the air density and Cd = .0012 .
In the present study, daily wind stress and heat flux for years1976, 1995, 1996 and 1997 have been utilized to force the regional model. These years were chosen to span a range of interannual variability in winds and freshwater input, and to overlap with the repeating cycle of NCEP winds used to force the global model. A comparison of computed low-pass filtered wind stress near Sitka, AK for the four years is presented in Fig. 5a. Note how the 1976 wind stress was especially strong and northwestward, relative to the other years.
Fig. 5.a) Low-pass filtered wind stress
near Sitka, AK (N/m2), computed from NCEP reanalyses.
2.3.3. Freshwater Input
Freshwater from distributed sources is
a major source of buoyancy to the CGOA. Time series of "line-source" freshwater
input are shown in Fig. 4 for 1995. These monthly values of integrated
freshwater runoff along segments of the coastline were derived from snowpack,
precipitation and temperature data by Royer (1982 and pers. comm.). The
data represent runoff from areas seaward of the coastal mountain range.
The "Southeast" region begins at the southern border of Alaska and extends
northward to a location between Glacier Bay and Yakutat Bay. The "Southcoast"
extends northward from there to include the southern side of the Kenai
Peninsula. These regions are roughly equivalent to 130W-141W and 141W-152W
longitude.
These line-source estimates were supplemented by river discharge data for significant inland areas draining into the CGOA. The river discharge data were obtained from USGS sources. The Susitna and Copper Rivers were among the few rivers that were gauged, and there were not many years of data for either. Therefore, a monthly climatology was computed with all the available data, and this is used for every model year. Peak mean values for river discharge occur in July. However, little discharge is provided by these large rivers (~10 percent of the total), relative to the line sources (~90 percent of the total). In Fig. 5b, we compare the total discharge from Southeast plus Southcoast regions plus river input for the four years noted in Fig. 5a. While the seasonal runoff pattern is similar between years, significant variability does exist, with especially wet months in September 1995 and November 1996, and an especially wet spring for 1997.
Fig. 5. b) Interannual comparison of total
monthly runoff from line-sources and river discharge, integrated along
the length of the CGOA. "Southeast" values were lagged by one month relative
to "Southcoast" values to obtain these totals, as in Royer (1982).
2.3.4. Mixing
Vertical mixing is parameterized as a function
of local shear and stability, using Mellor-Yamada level 2.0 closure (Mellor
and Yamada, 1974). Horizontal mixing of both scalars and momentum is calculated
with a biharmonic operator, and scaled by the local grid spacing as described
in Hermann and Stabeno (1996). Mixing is computed along geopotential surfaces,
rather than along sigma surfaces (Haidvogel and Beckmann, 1999).
2.3.5. Horizontal Boundary conditions
The philosophy of our approach to regional
modeling is similar to that of Hermann and Stabeno (1996), as follows.
True open boundary conditions are difficult to achieve in eddy-resolving
models, and especially so if tidal motions must be permitted simultaneously.
Open boundaries are notoriously unstable to vigorous mesoscale signals.
One sensible approach is to avoid open boundaries entirely through the
use of a telescoped grid and a simple closed box (Fig. 2). Within this
box, adjacent to the finely resolved area of interest, are placed bands
where flow and scalar values are nudged towards desired values, but not
so strongly as to prevent the escape of any out-going, internally generated
mesoscale signals. The desired boundary values may be based on data or
an externally run large scale model, or some combination of the two. The
area between nudging bands and the solid wall is intended to function as
a free recirculation zone, satisfying continuity and possibly absorbing
any mesoscale features which escape from the interior. When both tidal
and subtidal forcing is desired, a useful approach is to separately apply
the tidal signal on sea surface elevation in a nudging band adjacent to
the solid wall. If nudging constants for the subtidal nudging band are
chosen properly, the tidal signal will pass cleanly through that band without
interference. In the present work, we will show only results from the subtidally
nudged model. Future work will add simultaneous tidal forcing, as has been
accomplished for the Bering Sea (Hermann and Haidvogel, 2000)
2.3.6. Float Tracking
Ultimately our physical modeling system
will feed information to a three-dimensional lower trophic level (NPZ)
model, and an individual-based model of juvenile salmon. The NPZ model
is designed to include preferred prey of juvenile salmon (e.g. euphausiids),
and is currently running in one-dimensional (depth-time) form (Sarah Hinckley,
personal communication). As an intermediate step on the path to fully coupled
models, we are tracking representative fish (here, passive numerical floats)
using surface currents generated by the regional physical model.
Hartt and Dell (1986) reported high catches
of juvenile sockeye salmon in July centered at ~55 N 133 W, just northwest
of the Queen Charlotte Islands and within 40 km of the coast. Guided by
this observation, and in order to address how purely physical advection
of salmon (and plankton generally) might compare with their observed histories,
our floats are seeded in northwest-southeast lines at 0,100,200,300 and
400km from the coast between the Queen Charlotte Islands and Sitka. Subsequent
tracks are strongly influenced by the Sitka Eddy, as described in the results.
3. Model experiments
We have set up several model experiments
to test features of the coupling scheme and performance of the regional
model. The experiments conducted are as follows:
1) Run of the global model. The global
model is spun up with 5 years of a repeating cycle of daily NCEP winds,
spanning the period of NCSAT wind availability (Aug 1996-July 1997). Resulting
depth-integrated velocities were low-pass filtered and stored on a daily
basis, for use by the regional model.
2) Free runs of regional model. We spin
up the regional model from a state of rest, starting on January 15 of each
simulated year. Temperature and salinity fields are initialized with Levitus
climatology for January, and driven with winds, heat flux, and runoff as
described in the Methods section. Runs were executed for calendar years
1976, 1995 and 1997.
3) Nested (boundary nudging) runs of the
regional model. Here we utilize monthly climatologies (Levitus) for T and
S, and daily barotropic velocities from the global model, as candidate
fields to be applied to the nudging bands in the regional model. Wind,
heat flux and coastal buoyancy forcing is applied for the period August-December
1996, when applicable SEOM results are available.
3a) In the first assimilation experiment,
the regional model is nudged during July 27-Aug 1 with daily barotropic
velocities (from SEOM), and monthly T,S fields (from Levitus climatology).
A uniform nudging coefficient is applied in the finely resolved domain,
and ramped to zero approaching the outer edges of the (telescoped) domain.
This pattern of assimilation allows the interior to assume the SEOM velocity
values, without forcing any flows through the solid walls. Subsequent to
the five-day spinup, the model is nudged only in the telescoped domain,
with nudging coefficient values ramped to zero at the edge of the finely
resolved domain and at the outer walls of the telescoped area. The initial
spinup everywhere with SEOM provides the essential broad patterns of the
flow field, including some larger eddies. Subsequently the regional model
is free to develop finer-scale circulation in its interior, under the influence
of local wind and buoyancy forcing and with the SEOM velocities and Levitus
T,S applied as a horizontal boundary condition.
3b) In the second assimilation experiment,
the model is spun up as in case 3a). Subsequently, however, we remove all
influence of the SEOM velocities, and assimilate only the climatological
T,S as a horizontal boundary condition. By contrasting runs 3b) and 3a),
we clarify the influence of global barotropic velocities on the interior
regional solution.
4. Results
4.1. Global model results
Here we present barotropic velocities and free surface height fields from SEOM on a regular lat-long grid, for mid-July (Fig. 6) and early November (Fig. 7). Coastal and shelf-break currents are evident, as are meanders and eddies in the deep basin. A significant portion of the shelf-break current in the northwestern GOA (the Alaskan Stream) appears to come from the deep basin in these simulations, in addition to shelf-break currents upstream. In early November, a spatially continuous flow proceeds westward (counterclockwise) around the GOA. Results for mid-July exhibit a significant reversal of that near-coastal flow in the eastern GOA. Seasonal weakening/reversal of the coastal currents in the eastern GOA has been noted by Royer (1998) and is suggested by the analyses of seasonal altimetric patterns of Strub (2000). In both frames, the Alaskan Stream is wider and weaker than is typically observed, probably due to the limited spatial resolution and smoothed bathymetry of the model.
Fig 6. Global model SSH (shaded, m) and
barotropic velocity (m/s) for DOY 155.
Fig 7. Global model SSH (shaded, m) and
barotropic velocity (m/s) for DOY 304.
4.2. Regional model free run results.
4.2.1 Prominent features of the circulation and SST
Regional model results reproduce many of the major observed features in the CGOA (Figs. 8-10). In this section we examine 130-day runs initialized with Levitus climatological January T and S and driven with winds, heat flux and runoff appropriate to 1995 and 1997, respectively. Both runs exhibit a prominent AC-AS system and a weaker ACC; a weak ACC is appropriate for this time of year, as buoyancy fluxes are at their seasonal minimum. As in the global model results, the AS is weaker and somewhat wider than is typically observed; even finer than 22 km resolution would be required to improve this result. A general warming is observed in model results from early March through mid-May 1995 (Figs. 8 and 9), with some persistent cold areas near the coast. A tongue of warm water penetrates west along the shelf break in model results, as has been noted in SST images and in hydrographic data. A comparison of the simulations for 1995 versus 1997 (Fig. 10) reveals warmer temperatures in 1997. A similar degree of large eddy activity was observed in the May results for those two years.
Fig. 8. Regional model SST (shaded, degrees
C) and barotropic velocity (m/s) for DOY 64.5 1995.
Fig 9. Regional model SST (shaded, degrees
C) and barotropic velocity (m/s) for DOY 144.5 1995.
Fig 10. Difference in regional model SST
for 1997 vs. 1995 at DOY 144.5. Note the warmer temperatures in 1997, especially
at the location of the Sitka eddy.
Extensive mesoscale circulation features
are observed in model output, on the continental shelf, at the shelf break,
and in the deep basin. In the deep basin, many of these (modeled) features
are locked to prominent seamounts. Animated results exhibit a clockwise
propagation of disturbances around the seamounts. On the shelf, small eddies
with 50-100km diameter are produced, but appear less dynamic than has been
observed in drogued drifter studies (Stabeno and Hermann, 1996). During
the first week of March, 1995, the regional model exhibits an intense,
rapidly evolving, 200 km-scale eddy field along the shelf-break (Fig. 7).
The eddy sizes and locations generally correspond to those which have been
observed in AVHRR imagery for this period by Thompson and Gower (1998)
(temperature signals are less evident than velocity signals, however, in
the model result).
Eddy activity at the 200 km scale is most prominent in the vicinity of Sitka, AK. In the spring of each simulated year, its location is slightly north of the traditionally reported Sitka eddy (e.g. Tabata, 1982), moving slowly offshore (that is, southwest) from spring to fall (Fig. 11). This seasonal migration has been observed in the layered model studies of Melsom et al. (1999). The Sitka eddy has been reported in other studies as topographically generated (Swaters and Mysak, 1985), and has average surface currents of 15 cm/s, with a maximum of 110 cm/s as measured by drifters. Our regional model-generated surface drifter tracks for spring 1997 in this area (Fig. 12) compare favorably with observed drifter tracks reported in Tabata et al (1982), but do tend to exhibit weaker velocities than observed. Specifically, observed drifters transit the Sitka eddy in about 11 days, while the model's drifters require about 30 days to complete one circuit. Velocities shown in Fig. 11 also show a jet of offshore flow, feeding the eddy with coastal waters from the south.
Fig. 11. Regional model results for 1976:
SSH relative to areal mean (shaded, m) and surface velocities (m/s; for
clarity only every other vector is plotted) in the vicinity of Sitka, AK
for March (spring), June (summer), September (fall) and December (winter).
Note the gradual migration of the "Sitka eddy" offshore from Spring through
Winter 1976.
Fig. 12. Trajectories of surface drifters
in the vicinity of Sitka, AK, based on regional model output. Tracks begin
at large red asterisks on April 4, 1997. Small asterisks mark daily intervals
and end on May 24, 1997. Surface velocity on April 4, 1997 is marked with
blue arrows (m/s). Masked land area is shown in green.
4.2.2. Numerical Drifters
Numerical drifter tracks for July-Dec 1976 (Fig. 13 a-f) underscore the significance of the large eddy activity, and the Sitka eddy in particular, to salmon dynamics in the Gulf. Floats were initialized in a matrix parallel to the coast south of Sitka AK (indicated by asterisk in Fig. 13a), and subsequently tracked for July-Dec 1976. Half of the drifters released near the coast (Fig. 13b) become trapped in the Sitka eddy, with penetration further north only for tracks very close to the coastline. Drifters released 100km offshore (Fig. 13c) exhibit similar entrapment in the eddy feature. At 200km (Fig. 13d) offshore most of the drifters move around the western rim of the eddies; these either merge into the Alaskan Stream, traveling far to the west, or run aground between Sitka and Prince William Sound due to downwelling circulation (Fig. 5). Releases at 300 and 400km offshore (Fig. 13e,f) typically run aground somewhere between Yakutat Bay (east of Prince William Sound) and Cook Inlet (east of Kodiak Island).
Fig 13. a) Initial positions in float
tracking experiments using regional model surface velocities. Floats are
released to the south of Sitka AK (indicated by asterisk in figure), and
subsequently tracked for July-Dec 1976, with positions marked at half-daily
intervals. b-f) Float tracks subsequent to release nearshore (b), and at
100km (c), 200km (d), 300km (e), and 400km (f) offshore.
4.3. Nested run results
Here we compare: the global model (SEOM)
barotropic velocity results (experiment 1); a regional model run with boundary
nudging of both global barotropic velocities (from SEOM output) and T,S
climatology (experiment 3a); a regional model run with boundary nudging
of T,S climatology only (experiment 3b). Results of each case are presented
on the grid used by the regional model (in the case of the global model,
results from the unstructured grid were interpolated onto this regular
grid). Each of the regional model simulations was started on August 1,
initialized with the results of the 5 day spinup period previously described.
T,S climatology appropriate to that date. After 90 days, the velocities
associated with the SEOM fields have penetrated far along the coastal waveguide
and, to a lesser degree, into the interior of the basin. This is consistent
with the fast propagation of coastally trapped signals.
First, consider the global model results for early November 1996 (Fig. 14). As noted in previous figures, the velocities in the global model are generally weaker than those in the regional model. The Alaskan Stream is less well developed than in the regional model, and the Sitka region exhibits far less mesoscale structure than in the regional model. These results are expected; the layered model employs a coarser grid, smoother bathymetry and a less realistic coastline than the regional model in the CGOA, and has no buoyancy forcing. As such, it cannot be expected to generate as much mesoscale activity, or as vigorous currents, as the regional model.
Fig. 14. Global model (SEOM) barotropic
velocities (m/s) and speeds (shaded, m/s) for DOY 303 1996.
By contrast, the regional model for the corresponding day exhibits a stronger ACC and a near-coastal eddy field associated with the Alaska Coastal Current to the east of Kodiak Island (Fig. 15). As noted in Fig. 5, buoyancy forcing is typically strongest in the fall, hence eddy generation via baroclinic instability (abetted by a temporary weakening of the downwelling-favorable winds) is a likely source of these smaller eddies. Larger meanders near the shelf break (especially near Sitka) are also in evidence.
Fig 15. Regional model barotropic velocities
(m/s) and speeds (m/s, shaded) for DOY 303.5 1996. Global model barotropic
velocities and climatological T and S were used to spin up the regional
model for DOY 210, and were subsequently assimilated as a horizontal boundary
condition for DOY 210-304.
A closeup of the Sitka region exhibits an eddy feature just southwest of Sitka, as in other runs (Fig. 16). Velocities along large stretches of the coast and shelf break on this day (DOY 305) are southeastward, in contrast to the northwestward velocities of the global model (see Fig 14). This may be a reflection of the more accurate, shallower bathymetry of the regional model, with local daily winds exerting a stronger influence on the depth-integrated currents. Such current reversals have in fact been observed in Shelikof Strait and in the eastern CGOA during periods of upwelling-favorable wind (but are notably absent in other areas, e.g. Gore Point, just upstream of Kodiak Island; Stabeno et al., 1995a).
Fig. 16. Closeup of regional model velocities
and speeds in the vicinity of Sitka AK.
Boundary velocity information provided by the global model can be expected to influence the regional model most strongly near that boundary. Coastal-trapped waves, Rossby waves and simple advection can be expected to carry boundary information into the interior, as well. Indeed, one strong motivation for using global model results (or real data) at the boundary of the regional model is to provide just such information about remotely forced coastal-trapped waves to the regional model interior. Here we calculated the RMS difference in velocities between a 30-day run with boundary nudging of global model barotropic velocities and climatological T and S, versus a run with boundary nudging of climatological T and S only. The difference was normalized by the RMS velocity of the model run with boundary nudging of climatological T and S only (Figs. 17 and 18). This normalized difference is intended as an approximate metric for how much velocity signal is added to different regions of the interior through nudging at the boundary, relative to background velocity values. Large normalized differences were observed at the outer edge of the shelf slope, with much smaller values along the coast. Local maxima were observed in the vicinity of the Sitka eddy and in some portions of the deep basin, generally associated with topographic features. The relatively weak influence on near-coastal flows over the 30-day period may reflect the fact that only barotropic information is provided by the global model, whereas the true coastal current (that is, the ACC) has a strong baroclinic signature.
Fig. 17. Normalized RMS difference in
regional model barotropic velocities, averaged over DOY 214-244, for two
different boundary nudging schemes. In the first case, boundary nudging
includes both global model barotropic velocities and climatological T and
S. In the second case only climatological T and S were included.
Fig. 18. Closeup of RMS difference between
the two cases in the vicinity of Sitka AK.
5. Discussion and Conclusions
Our initial experiments with various configurations
of two circulation models for the Gulf of Alaska suggest that this area
can be realistically modeled using a regional scale model, but results
are strongly affected by the inclusion of boundary information from a global
model. These results are an important step towards our goal of exploring
the effect that interannual and decadal changes in GOA circulation have
on lower trophic level dynamics and fishery populations.
Our regional model with ~20 km horizontal
resolution and 20 vertical s-coordinate levels captures much of the spatial
and seasonal patterns GOA circulation. Both the AC-AS and ACC current systems
are easily identified in model output, though with somewhat reduced strength
than is observed in the environment. Seasonally, a weakening/reversal of
the coastal current in the eastern CGOA is observed. Interannual differences
are also evident between the different years simulated; for instance, spring
1997 has generally higher SST that spring 1995. This is important because
it implies that using this model, we will be able to investigate effects
of the physical regime shift that has been documented in the GOA system.
Barotropic information from the global
model can be effectively incorporated into this regional model as a boundary
condition, through the use of suitably designed nudging bands located outside
the region of interest. Spurious effects of rigid wall dynamics are avoided
by allowing free compensatory flow in the telescoped region outside the
nudging band. As presently constructed, this approach yields greatest short-term
(30-day) impact, relative to background velocities, in the AS-AC current
system at the outer edge of the shelf slope. Much weaker influence is felt
in the mainly baroclinic, near-coastal ACC. Significant impacts are observed
in the deep basin, generally associated with topographic features.
We believe these results can be further
improved by including the influence of baroclinic information from the
global model. Specifically, we plan to generate multiyear simulations with
the global layered model, and project information about the first baroclinic
mode from those results onto the first baroclinic mode of the regional
model in the nudging band. Tidal forcing will be added as well, to better
capture the spatial variability of vertical mixing in the GOA. Intensification
of current speeds to more closely match observed current magnitudes and
spatial focus of the AS-AC and ACC may require higher (for example, 10
km) horizontal resolution in the regional model. New regional model codes,
which take advantage of parallel computer architectures, will hopefully
allow these higher resolutions to be implemented for multiyear runs.
The model also captures the dominant 200
km scale variability observed in the Gulf. It displays especially strong
mesoscale dynamics in the vicinity of the Sitka eddy. The locus of this
activity migrates slowly offshore from spring through winter. The strength
of this feature is significantly affected by the upstream assimilation
of global model results.
Resolution of this eddy is particularly
relevant to salmon migration. The shelf in this area is very narrow, so
passing salmon would be particularly vulnerable here to offshore advection.
Modeled surface particles released directly upstream (that is, southeast)
of the Sitka eddy are typically captured or deflected by it for periods
exceeding one month. However, very close to shore, some particles move
northwestward along the coast, avoiding its influence, and the influence
of the offshore jet which is sometimes associated with the eddy in the
model results.
Hartt and Dell (1986) present a summary
of sockeye salmon migration patterns in the Northeast Pacific derived from
a detailed examination of catch data from coastal and high seas cruises.
This work stands as an important synthesis of the available data on salmon
distribution and migration patterns during the early phase of the salmon
marine life history. The coastal migration patterns of salmon are thought
to involve movement along a narrow band over the continental shelf (Hartt
and Dell 1986, Groot and Cooke 1987). A directed northwest swim bearing
during this time has been inferred based on higher net catches in seine
sets open in the direction of migration (Hartt and Dell 1986). These studies
have concluded that fish tend to exhibit ground speeds of approximately
18.5 km/d (Hartt and Dell 1986). Sockeye salmon migrate from coastal waters
adjacent to Sitka, AK to the Kodiak Island region over a six month period
during July to December. The timing and position of offshore migration
remains unclear, but is thought to occur in late winter and early spring.
Results from our simulations suggest passive
drifters greatly underestimate the net travel rate of salmon along the
coastal Gulf of Alaska. The most appropriate float track to compare to
observations of salmon migration are the ones released nearshore (Fig.
13b). While salmon appear to make forward progress at a rate of approximately
18.5 km/d, our surface floats in the simulation moved at a significantly
slower rate (~6 km/d). While the model itself may underestimate the true
current speeds, these fish in nature appear to exhibit relatively strong
compass bearing and directed swimming, and hence the discrepancy could
be explained by the fishes' innate ability to direct their movements while
migrating. The swim speed that would be necessary to account for this discrepancy
would be on the order of 12 km/d (or 13 cm/s, approximately 1.3 body length/s),
which is biologically plausible. Theoretical predictions of optimal swim
speed (speed that minimizes energy cost of locomotion per unit distance
traveled) for this size class of fish are in the range of 14-27 km/d (or
25-30 cm/s, approximately 2.5-3 body lengths/s, Webb 1995). This theoretical
prediction represents a more instantaneous rate, and thus is not directly
comparable to our measures of net travel rate that can include non-direction
movements along the migration path.
While several float tracks released nearshore
became entrained in the Sitka eddy, to our knowledge no one has identified
whether this oceanographic feature can entrain juvenile salmon. Depending
on the intensity of the currents, this eddy may have an influence on migration
timing, growth and survival of juvenile salmon. Further modeling efforts
are required to determine what impact this entrainment might have on migration
patterns, and if salmon swimming behavior can influence the risk of becoming
trapped in an eddy.
Acknowledgments
This research is contribution 2174 from NOAA/ Pacific Marine Environmental
Laboratory and contribution FOCI-0387 to NOAA’s Fisheries Oceanography
Coordinated Investigations, and was supported by the Joint Institute for
the study of the Atmosphere and the Oceans under cooperative agreement
NA67RJ0155, contribution #750. GLOBEC is sponsored by the National Science
Foundation and the Coastal Ocean Program of NOAA. The second author gratefully
acknowledges the hospitality and financial support of the Miller Institute
for Basic Research in Science received during a sabbatical visit to the
University of California, Berkeley. Support from the Arctic Region Supercomputing
Center is also gratefully acknowledged.
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Figure Captions
Fig. 1. Overview of circulation in the
Gulf of Alaska.
Fig. 2. Layout of quadrilateral elements
for our layered implementation of the Spectral Element Ocean Model (SEOM).
Structure within each quadrilateral is represented with a polynomial basis
set of order eight. The resulting average "grid spacing" is approximately
25 km around the periphery of the North Pacific Basin, and increases to
about 100 km elsewhere.
Fig. 3. Layout of the telescoped rectilinear
grid for our regional implementation of the S-Coordinate Rutgers University
Model (SCRUM).
Fig. 4. Smoothed bathymetry used for the
regional model simulations. In this and subsequent regional model results
figures, the axes are aligned with those of the model (that is, rotated
38 degrees relative to true north), and units are model gridpoints in the
two coordinate directions ("xi" and "eta"). Distance between successive
gridpoints is approximately 22 km.
Fig. 5.a) Low-pass filtered wind stress
near Sitka, AK (N/m2), computed from NCEP reanalyses. b) Interannual
comparison of total monthly runoff from line-sources and river discharge,
integrated along the length of the CGOA. "Southeast" values were lagged
by one month relative to "Southcoast" values to obtain these totals, as
in Royer (1982).
Fig 6. Global model SSH (shaded, m) and
barotropic velocity (m/s) for DOY 155.
Fig 7. Global model SSH (shaded, m) and
barotropic velocity (m/s) for DOY 304.
Fig. 8. Regional model SST (shaded, degrees
C) and barotropic velocity (m/s) for DOY 64.5 1995.
Fig 9. Regional model SST (shaded, degrees
C) and barotropic velocity (m/s) for DOY 144.5 1995.
Fig 10. Difference in regional model SST
for 1997 vs. 1995 at DOY 144.5. Note the warmer temperatures in 1997, especially
at the location of the Sitka eddy.
Fig. 11. Regional model results for 1976:
SSH relative to areal mean (shaded, m) and surface velocities (m/s; for
clarity only every other vector is plotted) in the vicinity of Sitka, AK
for March (spring), June (summer), September (fall) and December (winter).
Note the gradual migration of the "Sitka eddy" offshore from Spring through
Winter 1976.
Fig. 12. Trajectories of surface drifters
in the vicinity of Sitka, AK, based on regional model output. Tracks begin
at large red asterisks on April 4, 1997. Small asterisks mark daily intervals
and end on May 24, 1997. Surface velocity on April 4, 1997 is marked with
blue arrows (m/s). Masked land area is shown in green.
Fig 13. a) Initial positions in float tracking
experiments using regional model surface velocities. Floats are released
to the south of Sitka AK (indicated by asterisk in figure), and subsequently
tracked for July-Dec 1976, with positions marked at half-daily intervals.
b-f) Float tracks subsequent to release nearshore (b), and at 100km (c),
200km (d), 300km (e), and 400km (f) offshore.
Fig. 14. Global model (SEOM) barotropic
velocities (m/s) and speeds (shaded, m/s) for DOY 303 1996.
Fig 15. Regional model barotropic velocities
(m/s) and speeds (m/s, shaded) for DOY 303.5 1996. Global model barotropic
velocities and climatological T and S were used to spin up the regional
model for DOY 210, and were subsequently assimilated as a horizontal boundary
condition for DOY 210-304.
Fig. 16. Closeup of regional model velocities
and speeds in the vicinity of Sitka AK.
Fig. 17. Normalized RMS difference in regional
model barotropic velocities, averaged over DOY 214-244, for two different
boundary nudging schemes. In the first case, boundary nudging includes
both global model barotropic velocities and climatological T and S. In
the second case only climatological T and S were included.
Fig. 18. Closeup of RMS difference between
the two cases in the vicinity of Sitka AK.