Download Main upwelling regions in the Baltic Sea. ICES CM 2001/U:09

ICES CM 2001/U:09
“Not to be cited without prior reference to the author”
Session U “Mini-Symposium on Ecosystem Change in the Baltic”
Main upwelling regions in the Baltic Sea
By
Kai Myrberg1, Oleg Andrejev1, Eero Aro2, Juha Flinkman1 and Harri Kuosa1
1. Kai Myrberg, Oleg Andrejev, Juha Flinkman and Harri Kuosa: Finnish Insitute of Marine
Research, P.O.Box 33, FIN-00931, Helsinki, FINLAND [tel: +358 9 613 941, fax: + 358 9
613 94 494, e-mail:[email protected]].
2. Eero Aro: Finnish Game and Fisheries Research Institute, Pukinmäenaukio 4, P.O. Box 6,
FIN-00721 Helsinki, FINLAND [tel: +358 205751253,fax: +358 205751201,e-mail:
[email protected]]
Keywords: upwelling, modelling, statistical index, ecosystem
ABSTRACT
Upwelling is an important process e.g. in the Baltic Sea in bringing nutrient-rich waters to the
surface layers. Consequently, the surface layers are replenished with the nutritional components
necessary for biological productivity. The type of nutrient input - slow diffusion vs. periodic
upwelling – also affects on ecosystem structure, the latter leading to generally shorter food chains
with higher energy transfer to higher trophic levels.
Our present knowledge of the most important upwelling areas in the Baltic is inadequate and only a
few comprehensive investigations have been carried out to study these main regions. Here, threedimensional, high-resolution modelling is used as a tool to estimate the spatial and temporal
statistics of upwelling frequency in the Baltic during a 10-year period from 1979 to 1988.
According to the results of the simulations, a statistical upwelling index is calculated in order to
find the upwelling areas with highest persistency. A new idea is used here, where the key parameter
for determining the upwelling index is the vertical component of currents and not the changes in the
sea-surface temperature, as is usually done.
1. Introduction
The Baltic Sea (Figure1) is one of the largest brackish water areas in the world. It has a very limited
water exchange with the open ocean via the narrow and shallow Danish Sounds and is characterized
by a significant fresh-water surplus due to voluminous river runoffs. This leads to a two-layer
salinity stratification, which plays an important role for the physical processes. The currents in the
Baltic Sea are mainly caused by wind stress, even though thermohaline effects cannot be
disregarded. The sea-surface slope resulting from the permanent water supply due to river runoff
contributes appreciably to the existing circulation pattern. The Baltic Sea is very shallow having a
mean depth of only 55 m. Thus, the bottom topography plays a role modifying the physical
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processes and in spite of the comparatively small size of the sea, its various sub-basins are
characterized by quite different dynamics. The Baltic Sea has a meridional extension of about 650
km and a latitudinal extension of more than 1500 km. The complex physics of the sea and its
relatively limited size make it a challenging marine environment, a “marine laboratory”, which
allows us to study different physical processes by using measurements with a relatively high spatial
and temporal resolution. The measurements support model simulations in the form of good
verification material to test the models’ reliability in describing the physics of the sea.
Figure 1 The bottom topography of the Baltic Sea with corresponding sea depths in meters. The
scale of the colours is shown in the palette.
One of the key physical features in the Baltic Sea is upwelling. It is important process in bringing
nutrient-rich waters from the deep layers to the surface, in mixing water masses and in generating
frontal areas. During upwelling, the surface temperature can drop by about 10 degrees in a few days
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(Hela, 1976). The biological consequencies of upwelling can be significant. Thus, the surface layers
are replenished with the nutritional components necessary for biological productivity. The type of
nutrient input - slow diffusion vs. periodic upwelling – also affects on ecosystem structure, the latter
leading to generally shorter food chains with higher energy transfer to higher trophic levels. In spite
of its importance, not many papers have been devoted to the studies of upwellings in the Baltic Sea.
Gidhagen (1987) has carried out a comprehensive study of upwellings based on satellite images like
also did Bychkova and Viktorov (1986) as well as Kahru et al. (1995). A comprehensive study of
upwelling dynamics at the Finnish coastal areas by Haapala (1994) should be mentioned, too.
What is then the dynamics behind upwellings ? There can be found to be upwellings based on
different triggering mechanisms. The most typical one in the Baltic is a coastal upwelling.
According to Tomczak and Godfrey (1994) such a one occurs when the wind blows parallel to the
coast with the coastline on its left in the northern hemisphere. This produces a Ekman layer
transport directed 90 degrees to the right of the wind direction: this results in offshore water
movement. The associated lowering of the sea surface near the coast produces a pressure gradient
which is directed normal to the shore and drives a geostrophic current along the coast, in the same
direction as the wind. The effective water movement is the result of both wind-driven Ekman flow
and geostrophic flow. It is therefore directed at an angle away from the coast near the surface,
parellel to the coast at mid-depth (below the Ekman layer but above the bottom boundary layer) and
at an angle towards the coast in the frictional boundary layer at the bottom. The key factor for winddriven upwelling is the direction of the Ekman layer transport relative to the coast. Optimum
upwelling conditions are obtained when the Ekman transport divergence is maximized, which
occurs when the Ekman transport is directed offshore and normal to the coastline.
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Sometimes upwellings also take place at the open sea-area. This is due to the effects of bottom
topography or due to the curl of wind stress. However, in this paper the authors do not focus so
much on the detailed analysis of upwelling dynamics. The main idea is to carry out a statistical
analysis of upwellings in the Baltic Sea and find out the main upwelling regions and
correspondingly to define an upwelling index (see chapter 3). This is based on the idea to use the
model-produced vertical velcoity as the key parameter which shows the areas with the highest
persistency of upwellings; i.e. the main upwelling areas in the Baltic Sea.
We shall here use a three-dimensional, baroclinic hydrodynamic model (Andrejev and Sokolov,
1989; Sokolov, et al., 1997; Andrejev et al., 2000) to examine the upwelling characteristics of the
Baltic Sea. The idea is to simulate upwelling characteristics during the summer period, May to
September, which covers the period when main upwellings with potential biological consequences
to take place. The simulation period is 10 years; from 1979 up to 1988.
In next section we describe the implementation of the model as well as the data sets and forcing
functions which have been employed for the numerical experiments. The methods used for the
analysis of the upwelling and the index describing its persistency, are also dealt with. In section 3
the modelling results are discussed in some detail, whereafter the study is concluded by a summary
and a review of some practical consequences of the investigation.
2. Model implementation
The numerical model, which was developed by Andrejev and Sokolov (1989, 1990), is of the timedependent, free-surface, baroclinic, and three-dimensional variety. Simplifications in the form of
the hydrostatic approximation, the incompressibility condition, a Laplacian closure hypothesis for
sub-grid scale turbulent mixing, and the traditional f-plane approximation are made. It is
furthermore assumed that density variations only manifest themselves in the buoyancy terms;
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elsewhere the density is taken to be constant. The governing equations and the numerical methods
employed are not discussed here, because a comprehensive presentation of that can be found in
Andrejev et al. (2000).
2.1 Main parameters and assumptions
In order to apply the model, it is necessary to specify a number of quantities. The horizontal
kinematic eddy diffusivity coefficient µ is prescribed to be constant at 50 m2/s for the Baltic Sea.
The vertical eddy diffusivity coefficient ϑ is taken to be dependent on the local velocity shear and
buoyancy forces (Kochergin, 1987):
ϑ = (0.05h )
2
2
2
g ∂ρ
 ∂u   ∂v 
,
  +  −
ρ 0 ∂z
 ∂z   ∂z 
(1)
Where u and v are the velocity components along the eastward- and northward-directed x - and
y -axes, respectively. The z -axis is taken to point downwards, ρ is a density, ρ 0 is a reference
density and the gravitational acceleration is denoted by g . The parameter h is assumed to be 2.5 m,
which is equal to the thickness of the uppermost layer in the model (cf. sub-section 2.2).
The wind stress components (Niiler and Kraus, 1977) take the form
r
τ x = ρ a C d Wx W ,
r
τ y = ρ aCdWy W ,
where W is the wind velocity and ρ a is the density of air. Following Bunker (1977), the drag
coefficient C d at the sea-surface was formulated as
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C d = 0.0012(0.066 W + 0.63) .
(2)
A quadratic law was used for the bottom friction, where the drag coefficient C b was prescribed as
0.0026 (Proudman, 1953).
The heat transfer and radiation balance at the air-sea interface is, following Lane and Prandle
(1996), taken to be
FT = Qs + k (Ta − Ts ) ,
(3)
Where Qs is the mean solar radiation, Ta the air temperature, Ts the sea-surface temperature and k
an exchange coefficient. For salinity the corresponding flux Fs is to a lowest-order approximation
prescribed as zero, because the difference between precipitation and evaporation is not known
accurately due to a lack of observations. Fs is usually estimated to be slightly positive in the gulf,
but there are large discrepancies between the published estimates (e.g. Ehlin, 1981; HELCOM,
1986; Omstedt et al., 1997).
Even though no ice-drift mechanism is modelled, the effects of sea ice are taken into account since
for water temperatures below -0.2°C, the wind stress is decreased by a factor of 10, and at 0.0°C the
heat flux through the ice ceases as long as cooling conditions prevail. The reason for not reducing
the wind stress to zero is that “wind-stau” effects manifest themselves in the form of a tilting of the
ice-covered surface.
Vertical convection has to be parameterised since the model uses the hydrostatic approximation.
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The following heuristic algorithm is used: first a check is made of whether the water in a grid cell is
stable relative the water of the underlying cell. If not, the water of the unstable grid cell (or some
part of it, cf. Sokolov et al., 1997) is moved into the lower cell and the same volume of water from
the lower cell is displaced upwards and mixed with the upper-cell water. This procedure of water
replacement proceeds cell by cell until the sinking volume finds itself in stable conditions and the
water column is well-mixed in the vertical direction.
2.2 Set-up of the numerical model experiments
A 10-year period from 1979 to 1988 was investigated using the model. The simulation period was
yearly from May 1 up to September 30. This was due to the fact that the authors’ idea is to study
upwellings with biological relevance. The open boundary of the model domain is placed in the
Kattegatt along latitude 57°35′N. The horizontal resolution of the model is 2 nautical miles. For the
bottom topography we used a standard bathymetry provided by Seifert and Kayser (1995). The
Baltic model comprises 18 levels in the vertical with a monotonically increasing layer thickness
towards the bottom. The depths of the layer interfaces are: 0 m, 2.5 m, 7.5 m, 12.5 m, 17.5 m, 22.5
m, 27.5 m, 35.0 m, 45.0 m, 55.0 m, 65.0 m, 75.0 m, 85.0 m, 95.0 m, 105.0 m, 137.5 m, 162.5 m,
187.5 m and the bottom.
The initial temperature and salinity fields for model was assembled using a data assimilation system
due to Sokolov et al. (1997), which in turn is coupled to a Baltic environmental database (Wulff and
Rahm, 1991) and to the three-dimensional model employed here. To construct the initial fields for
May 1 each year (the first month of the numerical experiment every year is May), temperature and
salinity data from the database for all months of April from 1979 to 1988 were used. The reason for
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this somewhat artificial choice is the insufficient amount of true data available for a single April
month. The model run was initiated from a quiescent state.
We have used meteorological data for 1979-1988 with a spatial resolution of 1 degree for the entire
Baltic Sea area and a temporal resolution of 3 hours. Since the wind velocities in the data set
represent geostrophic values, they must be extrapolated to the sea-surface. A standard method for
this correction is to multiply the wind speed by a factor of 0.6 and deflect the direction 15° counterclockwise (Bo Gustafsson, pers. comm.). The long-term mean monthly river discharges (Bergström
and Carlsson, 1994) are used for the main rivers of the gulf (Neva, Narva, Kymi, Keila and Luga),
to which the contributions from smaller rivers are added.
2.3 The upwelling index
The upwelling index is defined as:
N
I=
∑w
n
∑w
n
n =1
N
n =1
× 100%
(4)
Where w is a vertical velocity, n (1….N) is the time step.
The index reflects a persistency of the vertical current component. If the vertical current is directed
upwards/downwards throughout the simulation period, the index is equal to 100% /-100%. The
more variable the direction of the vertical currents is, that closer the index is to 0%.
To remove high frequency oscillations, which could be generated by bottom topography, the fields
of upwelling indexes were filtered using Tukey cosinus-filter.
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f i , j = 0.28 f i , j + 0.13( f i , j +1 + f i , j −1 + f i +1, j + f i −1, j ) + 0.05( f i +1, j +1 + f i +1, j −1 + f i −1, j −1 + f i −1, j +1 )
(5)
Where subscripts i, j denote grid nodes, f is the filtered function.
3. The results of the numerical simulations
3.1 Main upwelling regions in the Baltic Sea
Due to the limited extension of the Baltic Sea, most of the upwelling events can be expected to take
place at the near-coast zone. The prevailing south-westerly winds are expected to play a certain role
in determining the spatial distribution of upwelling areas. We can also wonder how large values the
upwelling index, i.e. the persistency of upwellings, can reach in favourable areas.
Due to practical reasons, it is easiest to focus on the different sub-areas of the Baltic Sea separately
and to investigate the upwelling index and reasons behind the resulting patterns in detail. The
following figures represent the mean condition during the simulation from 1979 to 1988 (MaySeptember yearly). The investigation is concentrated on the depth of 2.5 m.
The upwelling/downwelling pattern becomes visible in the Bothnian Sea, even if the structure is not
so pronounced as in some other areas of the Baltic Sea. The mean wind conditions favour
upwellings to take place at the Swedish coast, while donwellings on average become visible at the
Finnish coast. The largest values of the upwelling index are about 30%, locally even up to 50 % and
typically between 5-15 % at the Swedish coast. Some interesting upwellings patterns are situated at
the southern Bothnian Sea with index of up to 20 %. These patterns are most probable connected
with bottom topography (Figure 2). The smallest values of the index are about -25% and typically
between –10 and –20 % at the Finnish coast representing downwellings.
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Figure 2. Upwelling/downwelling indexes in percentages in the Bothnian Sea (upwelling – positive
values, downwelling –negative values). The corresponding scale of the colours is shown in the
palette.
In the Gulf of Finland the dominating south-westerly winds favour upwellings at the Finnish coast
where the largest values of the index are about 30% and typically between 10-20 % (Figure 3). The
upwellings at the Finnish coast, especially near the Hanko Peninsula are well-known and welldocumented (Hela, 1976, Bychkova and Viktorov, 1986, Kononen and Niemi, 1986, Haapala, 1994
etc.). Upwellings also become visible at the mouth areas of some major rivers of the gulf. The
southern coast of the gulf is correspondingly characterized by downwellings. The smallest values of
the index are about –25 % and typically between – 10 and -20 %. A complicate mosaic-like
structure of the upwelling/downwelling system is seen at the open sea area. This pattern is most
probable coupled with bottom topography and to the circulation system (closed vortices) in the area.
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Figure 3. Upwelling/downwelling indexes in percentages in the Gulf of Finland and around the
Islands of Hiiumaa and Saaremaa.
The coasts of the Estonian Islands Hiiumaa and Saaremaa (Figure 3) are characterized by a same
kind of upwelling/downwelling system as the Island of Gotland. The upwelling is very intense
especially at the eastern coasts of Hiiumaa and Saaremaa with maximum index of about 25 % and
typical values between 10 and 20 %. At the west coast of both the Island strong downwelling takes
place with maximum index of about - 30% and typical values between -10 and -20 %.
Another area with pronounced upwelling/downwelling patterns locates around the Island of Gotland
(Figure 4). The south-westerly winds cause an upwelling to take place at the east coast of Gotland
with maximum index of about 30% and typical values between 10 and 20 %. The average condition
at the western coast is just the opposite, because the prevailing south-westerly winds cause a
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downwelling (maximum index of about -25% and typical values between -10 and -20 %). It should
be stressed that these patterns are results of a long-term calculation and do not represent necessarily
any single case. For example, if a northerly wind prevails, the pattern is opposite to that shown here.
The average situation is the same if the Island of Öland is investigated. The upwelling/downwelling
indexes are somewhat larger than in the case of Gotland. The dominance of the south-westerly wind
and related upwelling/downwelling patterns also become visible when studying the east and west
coasts of the Baltic Proper area: the west coast (Swedish coast) is characterized by upwellings while
at the eastern coast donwelling patterns dominate. The maximum index for upwellings are of about
40% and typical values between 15 and 30 %, while the maximum value for downwelling is –30%
and typical values between – 15 and –20 % correspondingly. An interesting general feature is that
offshore the coastal upwelling/downwelling areas, there is a opposite pattern (downwelling often
takes place offshore the coastal upwelling and vice versa).
Figure 4. Upwelling/downwelling indexes in percentages in the Baltic Proper.
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The Polish coast is mostly a downwelling area (with typical values between –10 and -20%), because
such a pattern is favoured by the prevailing south-westerly winds. At the western coast of the Bay
of Gdansk there is an upwelling region with maximum values of 40 % and typically between 15 and
30%. The surroundings of the Island of Bornholm are also characterized by upwelling/downwelling
pattern with maximum values of about 25 % and minimum of about –30 %. East of the Bornholm
there is an open-sea area with a downwelling with indexes between -10 and -20 %. This is most
probable conncetd with the overflow of water from the Bornhom Basin eastwards through the
Stolpe channel.
At the Danish Straits area pronounced upwelling conditions become visible. The whole east coast of
Denmark is an upwelling area. However, because the model’s open boundary locates near this area,
the detailed analysis is omitted here. The Danish Straits are charcerized by a pronounced
upwelling/downwelling system. In the narrow Öresund, the Danish side is an upwelling area and the
Swedish side a downwelling one. Same kind structures are found correspondingly in the Great and
Little Belt areas. The upwelling/downwelling structure is pronounced there; the upwelling index is
at most between 40 and 60 %, while the minimum values in the downwelling regions are between –
30 % and – 50 % (Figure 5)
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Figure 5. Upwelling/downwelling indexes in percentages in the Danish Straits.
3.2 Comparison with Gidhagen’s results
A comparison with the analyse of Gidhagen (1987) is carried out at the Swedish coastal area.
Gidhagen studied in situ data of temperature during a 10-year period of 1973-1982. Upwelling was
proved if an in situ measurement showed an abnormal temperature drop at least 2 ºC compared with
earlier and surrounding measurements. We calculated the upwelling index using eq. (4) for the
corresponding areas. The results are shown in Table 1. It becomes out that our results fit very well
with those of Gidhagen, even if the methods used were different from each others. This is
encouraging for the future work.
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Table 1. Upwelling frequency in percent of time (during 1973-1982) for some Swedish coastal
sections (Gidhagen, 1987) in comparison to calculated upwelling indexes (in parentheses).
Trelleborg
Ystad
Ratan
Bjuröklubb
Karlshamn
Kuggören
Kalmarsund
Sundsvallsb.
Landsort
Husum
Almagrundet
Fårö
Sv. Högarna
July, %
28 (28)
28 (21)
27 (23)
22 ( 5)
18 (25)
16 (18)
15 (14)
7 (12)
5 ( 7)
2 ( 7)
2 ( 8)
0 ( 4)
0 ( 1)
August, %
22 (25)
22 (22)
25 (12)
11 ( 8)
23 (22)
16 (14)
13 (15)
6 ( 4)
15 (14)
2 ( 2)
6 (12)
0 ( 2)
0 ( 6)
September, %
10 (23)
11 (11)
30 (15)
20 (14)
20 (22)
27 (24)
37 (32)
18 (12)
27 (27)
14 (10)
24 (23)
0 ( 5)
0 (5)
4. Discussion and conclusions
Up to now, the sea-surface temperature and its spatio-temporal changes have been used as indicator
for upwellings. However, the sea-surface temperature is most probable not the best indicator of
upwellings because it is determined by the heat balance and thus, turbulent mixing (both in
horizontal and vertical direction), advection and the interaction of the sea with atmosphere modify
the temperature variations in time. So, it is difficult to estimate which part of the changes in
temperature are really caused by true upwellings and which part is coupled with other
abovementioned factors. Additionally, if the water column is homogenous in terms of temperature,
the possible upwellings can not be found even if such ones occur and nutrient-rich waters are
brought to the surface indeed.
Due to the problems to use temperature as indicator for upwellings, the authors presented in this
paper a new approach where the vertical velocity at the near-surface layer is used as an indicator of
upwellings. A statistical analysis for a 10-year period was carried out (May-September yearly) and
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an upwelling index is defined to show (in percentages) which areas in the Baltic Sea are frequently
affected by upwellings (downwellings). Our present system does not take into account the speed of
the vertical velocity; all cases e.g. with a positive vertical velocity have the same weight in the
calculation of the index. In the future, it is possible to set a lower limit for vertical velocity and thus
only larger values than that would be taken into account in the statistics.
The statistical analysis clearly showed that the upwellings are mainly of coastal type and their
intensity is the largest, too. Open sea upwellings also occurs and in such a case the upwellings are
mainly caused by favorable shape of the bottom topography and/or due to the curl of wind stress. It
can be concluded that the main areas of coastal upwellings in the Baltic Sea are: The west coast of
the Bothnian Sea, the northern coast of the Gulf of Finland, the west coast of Baltic Proper, the east
coast of Gotland, east coasts of the Estonian Islands, east coast of Denmark including the Straits and
areas east of the Island of Bornholm.
The comparison with the analyse carried out by Gidhagen (1987) showed that there is a good fit
between the results, even if the methods in our studies very based on different ideas; Gidhagen’s
results were based on temperature while ours on vertical velocity and corresponding upwelling
index. It is encouraging for our future work that this comparisons gave good results. It should also
be remebered that the periods under investigation were not exactly the same.
Some additional remarks:
It became out that in many cases there exist a clear upwelling-downwelling structure perpendicular
to the coast. It means that if at the coastal area an upwelling zone exists, just offshore a
corresponding donwelling zone becomes visible and vice versa.
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It should be borne in mind that our study is a statistical approach of upwelling/downwelling
conditions; in some single case the upwelling/downwelling system can naturally be very different
from the results presented here.
The main upwelling areas are not exactly the same as those coupled with enhanced biological
acitvity (like algae bloomings etc) beacuse the sea currents transport and mix the water masses
continuously. Thus the nurient-rich, upwelled water massses move away from their original
location.
Acknowledgements
We would like to thank Prof. Mike St.John for suggesting to determine an upwelling index for the
Baltic Sea.
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