Abstract. Keywords: Oxygen deficiency, increased wind, oxygen model, the Kattegat, the Great Belt, vertical mixing, high-saline inflow.

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2 Abstract Using the hydrodynamic 3D model BSHcmod from the Danish Meteorological Institute coupled to an oxygen model from the same place, two simulations were performed modelling the oxygen concentration in the transition area between the Baltic and the North Sea. A reference simulation of the year 2005 was performed followed by the same simulation with the wind increased by 15 %. Results show that the area of oxygen deficiency, defined by concentrations below 126 mmol O 2 per m 3, decreased significantly from km 2 in the reference simulation to km 2 in the simulation with increased wind. The mechanism behind the increase in oxygen concentration between the two simulations is complicated, but the difference is probably mainly due to increased vertical wind mixing and to a smaller degree to inflow of oxygen-rich water from the Skagerrak, which mainly affects the Kattegat in the northern part of the area. It is clear however, that increased wind speeds overall causes an increased oxygen concentration in the water. Keywords: Oxygen deficiency, increased wind, oxygen model, the Kattegat, the Great Belt, vertical mixing, high-saline inflow.

3 Table of Contents 1 Introduction 2 2 Background Hydrography Stratification Mechanisms of mixing Wind General wind patterns over Scandinavia Forcing of flow by wind Oxygen Dynamics Annual cycle Effects on ecosystem 6 3 Method Hydrodynamic model Oxygen model Surface flux Pelagic sink Benthic sink Validation 10 4 Results Wind Overall oxygen deficiency in the Inner Danish Water Properties at single stations Oxygen content Salinity Re-oxygenation, Kattegat Re-Oxygenation, the Great Belt 21 5 Discussion Overall oxygen deficiency In- and outflows Station 1 and Station 3 and The oxygen model Relevance and improvements 27 6 Conclusion 28 7 Acknowledgements 29 8 References 30 1

4 1 Introduction Oxygen depletion has been recognised as a recurring problem in the inner Danish waters since the early 80 ies (Conley et al., 2007). Annual oxygen depletion has profound effects on the sea life in the affected areas in terms of lower biomass, lower density of fauna and lower diversity (Diaz and Rosenberg, 2008) and it also leads to the ecosystem being more vulnerable to another oxygen depletion event (Conley et al., 2007). Factors that affect the oxygen concentration of the waters are among others: Advection, entrainment and turbulence, the temperature, the export production, which depends on the availability of nutrients, the rate of respiration (Goldman and Horne, 1983) and the rate of decomposition by bacteria (Christensen et al., 2002). The wind speed over Scandinavia affects the flow through the Danish Straits and the mixing of the water (Abbott et al., 1976) and thereby also the oxygen concentration in the sea. In this thesis it will be investigated how a 15 % increase in wind speed will affect the oxygen conditions in the inner Danish waters by the help of the 3D hydrodynamic model BSHcmod from the Danish Meteorological Institute, coupled to a 3D model that calculates oxygen concentration in the water from the same place. Two simulations will be run for the year 2005, one for reference and one with 15 % extra wind, and it will be explored how the total area of oxygen deficiency changes through the year and between the simulations. First, an introduction to the hydrography of the Danish straits, to the wind s effect on the flow and to oxygen dynamics in the water will be given. Secondly, a short description of the model used will be given in the section Methods along with a description of the simulations that are to be performed and thirdly, the water s oxygen concentration in the simulations will be illustrated in the Results section along with salinity, temperature and wind strength. In order to be able to discuss the mechanisms behind the changes in the oxygen concentration, the development of oxygen concentration and salinity at four stations located in the northern and the southern Kattegat, the Great Belt and the Darss Sill will be shown. 2

5 2 Background 2.1 Hydrography The Baltic Sea, which extends from the Bay of Bothnia to the Skagerrak, can be regarded as a large estuary with the Danish Straits functioning as narrow sills (Stigebrandt, 2001). The inner Danish waters consist of the Belts, the Sound and the Kattegat. The Kattegat is mostly shallower than 15 meters, but along the Swedish west coast a channel has formed with a depth of 75 to 100 meters. The depth of the straits averages 20 meters (Leppäranta and Myrberg, 2009). To the south the area is bordered by the main sills of the Baltic; the Drogden in Oresund, which has a depth of 8 meters, and the Darss Sill at the entrance to the Belts from the Baltic, with a depth of 17 meters (Gustafsson, 1997). Towards the north, the Kattegat runs into the Skagerrak, and between the seas, the Kattegat-Skagerrak-Front is found (Gustafsson and Stigebrandt, 1996). It has been estimated that 80 % of the flow through the straits goes through the Belts and 20 % through the sound (Mattsson, 1996). Figure 1: Bathymetry of the modelled area 2.2 Stratification The location of the inner Danish waters, between the low saline Baltic Sea and the high saline Skagerrak, has the consequence that the Danish Straits are characterized by large vertical salinity gradients, but also by horizontal variations. In the vertical, the stratification typically creates two layers, with the inflowing high-saline Skagerrak water in the bottom layer and outflowing less saline Baltic water in the top layer (Stigebrandt, 2001). In the Kattegat this halocline is located at a depth of meters and in the straits approximately at 10 meters. This depth increases with stronger winds (Stigebrandt, 1983). The stratification is reinforced during the summer by the development of a thermocline (Abbott et al., 1976). Vertical mixing occurs to a large extend between the layers in the Danish Straits (Gustafsson, 1997). Upward entrainment is caused by the wind, and downward entrainment by the speed of the current in the bottom layer (Stigebrandt, 1983). In the Kattegat, the wind mixing dominates, thereby creating an upward entrainment, which according to Stigebrandt (1983) and Andersson and Rydberg (1993) has a velocity of approximately 0.25 meters per day. A consequence of the upward mixing is that the surface flow in the Kattegat has doubled compared to the flow in the straits and the salinity has increased when it reaches the Skagerrak (Gustafsson, 1997). When the flow enters the Belts, the narrowing causes the velocity to increase, which in turn increases turbulence between the layers and along the boundaries, and this generates a large degree of mixing in both directions (Pedersen, 1991). In the Oresund on the other hand, the Drogden sill is shallower than the main halocline, thereby blocking the flow and suppressing the vertical mixing with the consequence that water flowing to the Kattegat from the Oresund has a lower salinity than water 3

6 coming from the Belts (Pedersen, 1993). At the Darss sill, the water is forced over the sill at high speeds, and the resulting turbulence causes vigorous mixing (Gustafsson, 1997). 2.3 Mechanisms of mixing In a stationary turbulent flow with velocity u = ( u,v,w), the flow fluctuates around a mean, so it can be divided into a mean part, u, and a deviation from the mean, u': u = u + u' Wind blowing above a fluid causes frictional stress, τ w = Cd ρw u w u w on the surface of the fluid. This transfers energy from the wind to the water through the breaking of waves and shear flow (Csanady, 2001). Turbulent eddies of various sizes are created in the water and energy is cascaded from the large eddies to smaller ones through vortex stretching until the length scale is small enough for dissipation of energy to be important (Kundu and Cohen, 2008). The turbulence increases the contact between fluid parcels and thereby increases rate of diffusion and spreading of properties (Csanady, 2001). Mixing of water generates work against the buoyancy when eddy motion lifts heavier parcels of water upwards to where lighter water dominates. This causes an increase of potential energy in the water and consequently a loss in kinetic energy due to velocity reduction of the ambient flow. When a pycnocline is present, as is the case in the Danish waters, a larger amount of kinetic energy is required to mix the water across the density gradient, and this in turn means that stratification works to suppress turbulent motion (Cushman-Roisin and Beckers, 2007). When two layers have different velocities, as is the case in the Danish Straits, mixing takes place at the boundary between them as the different velocities create a shear flow, which cause turbulence, eddy motion and thereby entrainment of water from the slow to the faster moving layer (Csanady, 2001). 2.4 Wind General wind patterns over Scandinavia The westerlies, that are created by the pressure difference between the Azores high and the Icelandic low, are the background winds that are present as long-time mean at mid-latitudes. They are modulated by planetary waves and passing cyclones (Weisse and Storch, 2010). The dominant weather phenomena in Scandinavia are cyclones, which are created from atmospheric disturbances at the polar front (Bjerknes and Solberg, 1922). The cyclone propagates towards the east, and has a life cycle of about a week, during which it moves kilometres. Often cyclones form in families, with a new cyclone developing in the wake of the old one (Ahrens, 1994). The time it takes for a cyclone to pass the Danish Straits is approximately a day (Rohde, 1998), and when a cyclone is present above Scandinavia, winds from the west and south-west prevail (Gustafsson and Stigebrandt, 1996). The jet stream is modulated by planetary waves with wavelengths of 5000 to kilometres, oscillating around the earth at mid-latitudes and thereby affecting the climate here (Bogren, Gustavsson and Loman, 1999). One effect of the jet stream is that it forms anticyclones that are extensions of subtropical highs or are blocking anticyclones. These are more stable than cyclones and often stay a week or more over Scandinavia. Winds in anticyclones are weaker than in cyclones and are mainly from an easterly direction (Bogren, Gustavsson and Loman, 1999). Winds are generally stronger during the winter, as the pressure differences that drives the flow is higher at this time (Hurrel, 1995), (Ahrens, 1994) Forcing of flow by wind The flow through the Danish Straits is mainly controlled by barotropic and baroclinic pressure (Pedersen, 1991). The barotropic flow is generated by the difference in sea level between the Baltic 4

7 Sea and the Skagerrak, and this flow is modulated by baroclinic pressure due to the density difference between the brackish Baltic water and the high saline Skagerrak water (Gustafsson, 1997). During cyclonic activity the westerly winds cause an elevated sea level in the Skagerrak and a lower sea level in the southern Baltic. This creates a pressure gradient, which induces barotropic flow into the Baltic. The effect depends on the duration of the low pressure, the longer, the more water will be moved and the more new bottom water will enter the Baltic (Abbott et al., 1976). Inflows are correlated to the index of the North Atlantic Oscillation, (NAO), (Lehmann, Krauss and Hinrichsen, 2002) with a high NAO index indicating strong westerlies, which is a necessary prerequisite for inflow, and again, the stronger and longer lasting the wind, the stronger the inflow (Matthäus and Schinke, 1994). The connection with the wind strength also means that inflow mainly happens during the winter months with 90% of the inflow occurring between October and February (Schinke and Matthäus, 1998). Outflow through the Danish Straits happens in connection with anti-cyclonic activity above Scandinavia, which causes easterly winds, a higher surface level in the Baltic and thereby outflow. As high-pressure is more stable than low-pressure situations, outflow situations tend to be longer as compared to inflows (Abbott et al., 1976). 2.5 Oxygen When oxygen concentration in the water is low, marine life is affected through lower biomass, lower density of fauna and lower diversity (Diaz and Rosenberg, 2008). Oxygen deficiency is defined as a concentration of less than 4 mg/l or 126 mmol/m 3 and severe oxygen deficiency as less than 2 mg/l or 63 mmol/m 3 (Ærtebjerg, 2005). These limits have also been used to define oxygen deficiency in the present thesis. In Denmark, oxygen deficiency has been an area of interest since the early 1980 ies, when the water s oxygen concentration was found to be declining significantly (Conley et al., 2007). The Danish National aquatic monitoring and assessment program was implemented in 1988 (Conley et al., 2002), and this led to reversing of the upward trend in nutrient load that had been evident since the 1950 ies. The bottom oxygen concentrations through the summer have remained low however, something that can be explained by time lag, import and physical factors such as wind and temperature (Conley et al., 2007) Dynamics When the water is stratified, only little exchange of oxygen and nutrients takes place between the layers. In the top layer the oxygen concentration is usually relatively high as wind mixes oxygen from the atmosphere into the water and light penetration makes oxygen production by photosynthesis possible (Sand-Jensen and Lindegaard, 2004). Below the compensation depth, which in Kattegat is situated at approximately 14 meters (Pedersen, 1993), respiration dominates over photosynthesis and the water below this depth is therefore dominated by negative production (Sand-Jensen and Lindegaard, 2004). As the compensation depth coincides with the depth of the halocline in the Kattegat, the oxygen concentration in the bottom layer will slowly decline unless new oxygen is supplied by advection or by strong winds that are capable of disrupting the stratification (Pedersen, 1993). When the water in the bottom layer is oxygenated, the oxygen penetrates a few millimetres down in the sediment, and bacteria in the water and in this upper layer of the sediment use oxygen as an oxidizing agent to decompose organic material. Deeper down in the anoxic part of the sediment, other oxidizing agents are used in the following order: Nitrate (NO 3 - ), manganese (Mn 4+ ), iron (Fe 3+ ), sulphate (SO 4 2- ) and finally, when no oxidizing agents are available, methane production occurs. When oxygen depletion takes place above the sediment, the anaerobic front moves up in the water, and if no oxygen is supplied, the other oxidizing agents will be used. Sulphate oxidation creates hydrogen sulphide which is a toxin that kills the marine fauna by binding to haemoglobin. When methane production eventually takes place in the sediment, gas pockets are created, which, 5

8 when released, causes even larger releases of hydrogen sulphide, which again causes fish death higher in the water column (Christensen et al., 2002). Decomposition by bacteria in the bottom water remineralizes the nutrients, that can be reused in photosynthesis if they are brought to the photic zone (Mann, 2000) Annual cycle Oxygen deficiency usually takes place during late summer and fall in Danish waters (Conley et al., 2007), and this can be explained by the following mechanism: In wintertime photosynthesis, and thereby primary production, is limited by light, but strong winds cause a high degree of mixing, making nutrients available throughout the water. In the Kattegat, the concentrations of nutrients in the surface water increase from November to February (Andersson and Rydberg, 1988). In the spring, increased river runoff lowers the salinity of the out flowing Baltic water, thereby strengthening the halocline in the transition zone, which has the effect that the wind no longer provides adequate energy mix to the water to the same depth as in the winter, and a shallower pycnocline is created. When the depth of the pycnocline is above the critical depth, primary production begins to take place to a higher degree and the spring bloom begins (Mann, 2000). In the Kattegat this happens in the month of March (Nielsen and Hansen, 1999). The spring bloom creates a large mass of organic material, which eventually sinks to the bottom layer, where respiration and decomposition of the sinking organic material takes place using oxygen. Also, the higher water temperature in the summer causes lower solubility of oxygen in the water (Goldman and Horne, 1983) and it increases the speed of the metabolism of marine organisms (Clarke and Fraser, 2004). In the summer, the wind is generally weak and the stratification is strong. These factors, along with the lower solubility of oxygen and the higher metabolic speed of the marine fauna, mean that oxygen deficiency may develop. In the autumn, increased wind strength causes increased vertical mixing and increased high saline inflow from the Skagerrak, which again provides oxygen rich water to the bottom (Mann, 2000) Effects on ecosystem The sensitivity of different species to oxygen deficiency differs, and depends among other things on the size and level of activity of the animal. Fish have a tolerance level of about 126 mmol O 2 /m 3, whereas marine worms (Polychaete) tolerate levels down to 3.15 mmol O 2 /m 3. Benthic animals, such as crustaceans, have a tolerance level of approximately 63 mmol O 2 /m 3 (Hansen, Josefson and Carstensen, 2003). If new oxygenated water is not supplied, oxygen content in the pore water of the sediment is used for oxidation by bacteria that then change to anaerobic respiration. As oxygen concentration in the water falls, the fauna starts changing behaviour (Christensen et al., 2002); when oxygen concentration in the water falls below 126 mmol O 2 /m 3, fish will migrate upwards towards water with higher concentrations. When it falls below 63 mmol O 2 /m 3, the benthic fauna is affected; Crustaceans will move and borrowed animals, such as mussels seek upwards in the sediment (Diaz and Rosenberg, 2008). If hydrogen sulphide is eventually produced and released from the sediments, the gas reaches higher in the water column with the capability of killing all fauna. When this happens dead fish will start washing ashore and the ecosystem has been completed wiped out (Christensen et al., 2002). In the present thesis the definitions used for oxygen deficiency and serious oxygen deficiency are 126 mmol O 2 /m 3 and 63 mmol O 2 /m 3 respectively. When oxygen deficiency recurs annually, as is the case in Danish waters, the ecosystem must restore itself in between these events. The oxygen pool in the sediment needs to be refilled, something that is induced bioturbation, and therefore happens slower when burrowing animals are gone. If the oxygen pool has not been fully restored prior to the next onset of oxygen deficiency, the sediments will be more vulnerable to a new oxygen depletion event as the anaerobic zone is closer to the surface in this situation. If larvae have been killed due to lack of oxygen, animal density will be lower the following year (Rydahl, 2004). Lower biomass is a consequence of the time in between 6

9 periods of oxygen depletion being too short for the fauna to reach the adult stage, and therefore animals are smaller as compared to a healthy population. Low oxygen levels might also have the effect of inhibiting growth, which again lowers biomass (Hansen, Josefson and Carstensen, 2003). When periods of oxygen depletion are repeated annually, the composition of the ecosystem will change as the species that are tolerant to low oxygen levels will increase and the diversity decrease, an example of which has been observed in the Danish Straits, where the diversity of benthic fauna in 2007 was about half the value of the mid 1990 ies (Dahl and Josefson, 2009). In conclusion, repeated oxygen depletion will cause lower biomass, lower density of fauna and lower diversity, which in turn leads to the energy flow downwards to microbes instead of upwards to macro life (Diaz and Rosenberg, 2008). 7

10 3 Method The oxygen conditions in Danish waters are simulated using the 3D hydrodynamic model, DMI- BSHcmod coupled to an oxygen model. Two simulations are performed, each lasting one year, and both using initial values from December 30 th The reference simulation, which is hereafter referred to as Simulation a, is a simulation of actual conditions in The other, which is hereafter referred to as Simulation b, simulates the conditions of 2005 with the wind strength increased by 15 %. In Denmark, such an increase can be used as a reference to describe interannual variations. 3.1 Hydrodynamic model The 3D hydrodynamic model used in this study, DMI-BSHcmod, is a finite difference model which was first developed by the Bundesamt für Seeschifffahrt und Hydrographie in Hamburg, Germany and has since then been further developed at DMI. It includes description of sea level, temperature, salinity, currents and ice cover. The model domain, which is shown in Figure 2 below, has a horizontal resolution of 6 nautical miles and a vertical resolution of 50 layers. A fine grid model, which is illustrated in Figure 8 on page 14, covers the Danish Straits from Skagen to Bornholm with a horizontal resolution of 1 nautical mile and 52 layers in the vertical. The circulation model is forced with data from the meteorological model DMI-HIRLAM. Fresh water supply and energy fluxes are also taken into account in the model (Huess and Nielsen, 2009). The model uses spherical coordinates, and applies the Boussinesq and the hydrostatic approximations in the equations (Larsen, 2006). Figure 2: Area covered by the hydrodynamic model. The wind affects the flow in the model through the horizontal wind vector, u wind = ( u wind,v wind ), that denotes 10 meter wind speed and controls the wind stress,τ, in the following way: τ u wind = C d ρ wind u effective u effective Eq. (1) Where u effective = u wind u water. 8

11 A k-ω two-equation model is used to calculate turbulence, which is thereby mainly controlled by the velocity of the water and uses bottom- and surface stress as boundary conditions (Lars Jonasson, personal communication). 3.2 Oxygen model The oxygen model used in this study is implemented into the fine grid of the hydrodynamic model and boundary conditions of oxygen concentration in the water at Skagen and Bornholm are given by saturated values for oxygen based on observations. Oxygen concentration is designated mmol/m 3. In the model, pelagic respiration is taken into account all through the water column, whereas the air-sea flux of oxygen only occurs in the surface layer. In the deepest layer of the grid, benthic respiration and respiration by microorganisms in the sediment also plays a role. Equations are described below. The model is based on the assumption of a temperature dependent respiration, and the oxygen concentration is thereby modelled by a complex hydrodynamic model and a simple oxygen model. Apart from respiration and diffusion, oxygen levels are changed by currents causing advection, vertical mixing, salinity, temperature and density. Values for these are imported from the hydrodynamic model (Lars Jonasson, personal communication) Surface flux oxygen: For the surface layer in the model, the following equation is used to calculate air-sea flux, F O2, of F O2 = V( b C O2 sat C O2 ) Eq. (2) The piston velocity, V, is here set to 5 m/day. In reality the piston velocity is wind dependent, but simplifying it to a constant has no large effect on the results in the model. The bubble factor is set to b = C O2 sat denotes saturated oxygen concentrations, which are controlled by temperature and salinity, and C O2 denotes the concentration at the time in question (Stigebrandt, 1991) Pelagic sink The pelagic sink affects the oxygen concentration throughout the water column and consists of a constant oxygen consumption due to respiration which is modified by oxygen concentration and temperature dependence (Rasmussen et al., 2003): dc dt O 2 ( pelagic) = R w C O 2 C O 2 + K s water Q temp 4 C Eq. (3) Here, R w denotes the rate of respiration in the water and has a constant value of R w = ( mol O 2 )/( m 3 s). K s is the half saturation constant with the value K s water = and Q 10 is the change of oxygen consumption when the temperature is raised by 10 degrees. Here, Q 10 = Benthic sink In the bottom layer of the model, the oxygen sink consists of the sum of the pelagic sink and the benthic sink. The pelagic sink is described above and the benthic is described by equation (4) (Rasmussen et al., 2003): 9

12 dc dt temp 4 C O2 O2 10 ( benthic) = Rb Q CO + K s benthic 2 C CO 2 10 Rm Eq. (4) C O sat 2 The first term of the right hand-side describes the benthic respiration and the second describes the respiration by microorganisms, which is controlled by diffusion into the sediment; the higher the oxygen concentration above the sediment, the higher the diffusion rate and oxygen consumption in the sediments. R b = ( mol O 2 )/( m 3 s) is the benthic respiration, K s benthic = is the benthic half saturation constant and R m = ( mol O 2 )/( m 3 s) is the respiration by microorganisms Validation The model has been validated using measurements from the National Environmental Research Institute in Denmark and the Swedish Meteorological and Hydrological Institute The hydrodynamic model overestimates the temperature of the bottom water in the Kattegat and the Great Belt, possibly due to inadequate modelling of the vertical wind driven mixing. This has the consequence that the oxygen consumption, which is exponentially dependent on temperature, is overestimated in this area. This leads to the oxygen deficiency predicted by the model being more widespread than what is the case in reality. The temperature also affects the boundary conditions for oxygen concentrations in the model. These are defined as saturated values for oxygen, which become lower as the temperature is lowered, and they are thereby underestimated, which again leads to the oxygen concentration being underestimated. In the rest of the area in the Danish waters the model has been shown to give good results. Some results from the validation is shown in Figure 4. Figure 3: Position of stations for validation in the Kattegat, the Great Belt and the Little Belt. 10

13 Figure 4: Development of oxygen concentration at stations in the Kattegat, the Great Belt and the Little Belt from January 2005 to October Red dots are measurements and lines values predicted by the model (Lars Jonasson, personal communication). 11

14 4 Results The present section will start out with an overview of the wind strength through the year and then proceed to the location and development of the area of oxygen deficiency in the Danish waters. A closer look will be taken on stations 1 to 4 in terms of oxygen deficiency and salinity changes during the year, and finally, the changes in the water s properties in connection with the re-oxygenation of the water in the autumn at stations 1 and 4 will be investigated. Position of the stations can be seen in Figure 8, page Wind Figure 5: Maximum wind speed, monthly mean wind and mean bottom temperature in the area covered by the oxygen model illustrated for simulation a and b. Means are taken over the whole of the modelled area and all variables are shown for the year Figure 5 shows how both the mean wind and maximum wind in the modelled area is highest during the winter. The area was hit by a hurricane on the 8 th of January and by a blizzard on the 13 th of February (Theilgaard, 2005), which can also be seen in the figure with wind speeds higher than 30 m/s in January and 25 m/s in February. High wind speeds also occur in both simulations on the 25 th of October with 20.4 m/s, on the 16 th of November with 20.2 m/s and on the 16 th of December with 21.1 m/s. The minimum temperature of approximately 1 C is reached on the 7 th of March and the max temperature of approximately 6 C in mid September. 12

15 4.2 Overall oxygen deficiency in the Inner Danish Water Figure 6: Distribution of oxygen concentration at the bottom of the Inner Danish Waters on the 5 th of October Red areas are affected by serious oxygen deficiency and orange areas by less serious oxygen deficiency. Concentrations can be seen in the colour bars. a) Results for simulation a, b) Results for simulation b. According to the model, the day with the largest extent of oxygen deficiency in 2005 was the 5 th of October. In Figure 6a the distribution of the oxygen deficiency of simulation a is illustrated for this day, and it can be seen how it covers the South Eastern Kattegat, the Little Belt, the Lübeck Bay, the Great Belt, the Oresund and the Arkona Basin. Serious oxygen depletion mainly affected the Southern Little Belt, Lübeck Bay and the Arkona Basin. Simulation b (Figure 6b) shows that areas affected by oxygen deficiency are reduced to the South eastern Kattegat, and a smaller area of the Little Belt and the Arkona Basin when the wind is increased by 15 percent. Through the year, the areas affected by oxygen deficiency for the longest time in simulation a are the Little Belt, Lübeck Bay, the Arkona Deep and the south-eastern Kattegat. In simulation b, the distribution of oxygen deficiency is confined to smaller parts of these areas except for Lübeck bay where the water is now oxygenated. The areas affected by oxygen deficiency in simulation b, generally have a higher oxygen concentration than the corresponding areas in simulation a. The only exceptions are small parts of the Kattegat south of Anholt and the southern Arkona Basin. 13

16 Figure 7: Development of total area of oxygen deficiency in the Inner Danish Waters for the year 2005, along with the development of the area with an oxygen concentration between 63 and 126 mmol/m 3 and the area with a concentration below 63 mmol/m 3. Wind speeds higher than 13 m/s are marked by vertical grey lines. Note the different scales. a) Simulation a b) Simulation b. In Figure 7 it can be seen how the area of oxygen deficiency increases from early July and reaches its maximum on the 5 th of October in simulation a and on the 27 th of September in simulation b, after which it rapidly falls again. The total area of water covered by the oxygen model (Figure 6) equals km 2 and in simulation a, km 2 or 38.8 % of the total area of water is affected by oxygen deficiency on the 5 th of October. In simulation b (Figure 7b) the maximum area affected by oxygen deficiency is km 2 or 15.6 % of the total area. In both simulations, the area affected by less serious oxygen deficiency is larger than the area affected by more serious oxygen deficiency. In simulation a, the maximum size of the area covered by less serious oxygen deficiency is km 2 or 28.6 % of the total area, as compared to 8997 km 2 or 12.8 % affected by more serious oxygen depletion. In simulation b the numbers are 9295 km 2 and 2624 km 2 or 13.2 and 3.7 % respectively. The maximum of the area of serious oxygen in both simulations occur later than the maximum of less serious oxygen deficiency but both areas decrease at the same time. In both simulations, the area of oxygen deficiency decreases when a period with a high frequency of winds above 13 m/s starts in November. 4.3 Properties at single stations The position of the single stations can be seen in Figure 8. The depth at the stations is 61, 37, 28.5 and 18.5 meters respectively at station 1 to 4. Figure 8: The area covered by the oxygen model. Stations are placed at white diamonds numbered

17 4.3.1 Oxygen content Figure 9: Development of oxygen concentration from the surface to the bottom at the stations. Black line shows the contour of the oxygen concentration equalling 126 mmol/m 3. Results for simulation a can be seen in the left column and for simulation b in the right column. The same scale of oxygen concentration is used for all subplots but the depth at the stations differs. Figure 9 shows how the oxygen concentration in the water column is generally higher in simulation b as compared to simulation a. In simulation a, oxygen deficiency develops at all stations during late summer and autumn, the longest lasting being at station 3 in the Great Belt. The station experiencing the lowest oxygen concentration is station 4 at the Darss Sill. In simulation b, oxygen deficiency only develops at station 2 in the southern Kattegat, and the duration and distribution is smaller than what is the case for the same station in simulation a. At all 15

18 stations and both simulations, apart from station 4 in simulation b, the water is stratified with respect to oxygen during the summer and fall. Figure 10: Mean oxygen concentration in the water column at the stations for both simulations. Values are obtained by integrating the oxygen concentration from the surface to the maximum depth and dividing the result by the maximum depth at the station. The mean oxygen concentration at the four stations rises in the first two months of the year, reaches a maximum in late February or March and then falls until a minimum is reached between August and November (Figure 10). The largest mean concentrations occur at stations 3 and 4 with values above 400 mmol/m 3 and at station 1 and 2 the maximum concentrations are approximately 350 mmol/m 3. At station 1, the two simulations have equal values for oxygen concentration throughout the year except that re-oxygenation in October happens earlier in simulation b. At station 2 and 3, the oxygen concentrations of simulation b are consistently higher than in a from early spring throughout the year but following the same path as in simulation a. The oxygen concentration at station 4 is close to being equal in the two simulations, with the concentration being slightly higher in simulation b from June, and more smooth than in simulation a. 16

19 Figure 11: Oxygen concentration in the bottom water for both simulations. The grey dashed line marks the limit of 126 mmol/m 3 and the grey line marks the limit of 63 mmol/m 3. In Figure 11 it can be seen that bottom oxygen concentrations peak between February and May at all stations, after which it falls and reaches a minimum in late September or October and then again rises. The concentration falls below the limit of 126 mmol/m 3 at all stations in simulation a and at station 4 it also comes below 63 mmol/m 3 in October as seen in Figure 11d. In simulation b the oxygen concentration only falls below 126 mmol/m 3 at station 2. 17

20 4.3.2 Salinity Figure 12: Development of salinity through the water column at the stations. Results for simulation a can be seen in the left column and for simulation b in the right. Notice that different scaling is used at the different stations. The water is stratified with respect to salinity through most of the year at the Kattegat and Great Belt stations, with the salinity being above 30 psu at the bottom and between 10 and 18 psu at the surface (Figure 12). At the Darss sill (station 4) in simulation a, stratification develops in late April and persists until early November, with a shallow bottom layer. In simulation b the water is nearly completely mixed throughout the year (Figure 9h). For all stations, salinity of the surface water and the depth of the halocline is lower in simulation a than in simulation b. 18

21 Figure 13: Bottom salinity through the year at all stations for a) Simulation a and b) Simulation b. Figure 13 shows how the bottom salinity falls and becomes less stable from station 1 to 4. At station 1, simulation a, the difference between the lowest and the highest salinity is 1.25 psu and for station 4 it is psu. The corresponding numbers for simulation b are 1.59 and psu respectively. Figure 14: Mean salinity in the water column at all stations for both simulations. Values are obtained by integrating the salinity from the surface to the maximum depth and dividing the result by the maximum depth at the station. Figure 14 shows how the mean salinity in the water column falls from station 1, which is furthest towards north, to station 4 in the south. The yearly mean salinity is lower in simulation b at all stations with the largest difference being at station 3. At all stations, a clear peak appears in January followed by a decrease in salinity. A peak in salinity can also be seen at all stations in March and in late October or early November Re-oxygenation, Kattegat At station 1, re-oxygenation of the water takes place in October in both simulations (Figure 11a). The changes in the water in terms of oxygen concentration, salinity, wind stress, depth and strength of the stratification during this time will further be illustrated in this section. 19

22 Figure 15: Development of bottom oxygen concentration and bottom salinity in October 2005 at station 1, Læsø, for both simulations. The bottom oxygen concentration and salinity at station 1 rise simultaneously in both simulations ( Figure 15). In simulation a this happens between the 19 th and the 23 rd of October and in simulation b the change in oxygen concentration takes place between the 7 th and the 23 rd of October and salinity change occurs from the 5 th to the 23 rd of October. Figure 16: Development of wind strength at station 1 in October 2005 for both simulations. Bottom oxygen concentration is plotted for reference. The rise in bottom oxygen concentration in simulation a coincides with a rise in wind strength from approximately 1 to 14 m/s between the 18 th and the 19 th of October (Figure 16a). In simulation b an increase in wind speed from 0 to 14 m/s occurs between the 5 th and the 9 th of October, and during this increase, the oxygen concentration also increases with 60 mmol/m 3 ( Figure 16b). As the wind decreases, the increase in oxygen concentration continues to a smaller degree, but again increases as the wind again comes above 15 m/s. 20

23 Figure 17: Depth of the stratification defined as the depth at which the maximum change in density pr meter occurs in the water column, and the strength of the stratification at that depth shown for station 1. Figure 17 shows how the depth of the pycnocline in simulation a goes from 23.5 meters to 17 meters between the 11 th and the 15 th of October, and again falls on the 23 rd. Simulation b follows the same pattern, but it is located deeper in the water, between 31 and 19.5 meters. The strength of the pycnocline is slightly higher in simulation a, and in both simulations peaks occur on the 3 rd, the 13 th and the 25 th of October Re-Oxygenation, the Great Belt At station 3 in the Great Belt, re-oxygenation happens less abrupt than what is the case at station 1, so here the focus has been put on the period between the 1 st of October and the 30 th of December Figure 18: Development of bottom oxygen concentration and bottom salinity from October to January 2005 at station 3 in the Great Belt for both simulations. Bottom oxygen concentration and salinity are mirror images of one another in both simulations; an increase in oxygen concentration is accompanied by a decrease in salinity (Figure 18). In simulation a the oxygen concentrations are lower and the salinities higher than the corresponding values in simulation b. Figure 19: Development of wind strength at station 3 in the Great Belt from October to January 2005 for both simulations. Bottom oxygen concentration is plotted for reference. 21

24 Figure 19 shows no clear connection between local high wind strengths and rise in oxygen concentrations. Figure 20: Depth of the stratification defined as the depth at which the maximum change in density pr meter occurs in the water column, and the strength of the stratification at that depth shown for station 3 in the Great Belt. Figure 20a shows how the depth of the pycnocline and the strength of it at station 3 in simulation a to some degree mirrors one another with a depth of the pycnocline high in the water column corresponding with low strength of stratification. The strongest stratification occurs on the 8 th of November with a value of 3.7 kg/m 4. In simulation b the depth of the pycnocline averages 18 meters from October to late December. Low values of the strength of the stratification occur on the 28 th of October, the 16 th and the 22 nd of November and from the 24 th to the 30 th of December. 22

25 5 Discussion The area and duration of oxygen deficiency has been decreased by the wind increase of 15 %, and generally, the oxygen concentration of the water has increased. As will be discussed below, the mechanisms behind this are earlier inflow of oxygen-rich water from the Skagerrak and increased wind driven vertical mixing. The first mechanism is more important in the Kattegat and the second in the Belts. The change in oxygen conditions shows that marine life in the area, especially the benthic fauna that is less susceptible to oxygen deficiency, benefits from increased wind strength. 5.1 Overall oxygen deficiency Increased vertical mixing would make the bottom temperature in simulation b lower than in simulation a during winter and higher during summer, and Figure 5 illustrates how this is actually the case, so vertical mixing does indeed take place to a higher degree in simulation b. This provides oxygen-rich surface water to the bottom and explains why the water in this simulation generally has a higher oxygen concentration than what is the case in simulation a. Increased vertical mixing is also supported by the fact that the decrease in the area of oxygen deficiency mainly occurs at the shallower places where less energy is needed for vertical mixing to take place. In both simulations, oxygen deficiency develops from July and decreases again in late October (Figure 7). This timing can be explained by a combination of wind and temperature. The mean wind speed is at its lowest from May to October (Figure 5), which means that wind induced vertical mixing happens to a smaller degree during these months, providing less oxygen to the bottom water and enabling a stronger pycnocline. In the southern Kattegat and the Great Belt (station 2 & 3), this onset of the halocline occurs in March (Figure 12), which separates the bottom water from the surface water and thereby further inhibits oxygenation of the bottom water. Later in the year, in these simulations presumably from mid- October, the stability of the pycnocline decreases as a higher frequency of strong winds helps erode the stratification and consequently a lower wind speed is subsequently needed to mix the water and provide oxygen-rich water to the bottom. Also, the pycnocline becomes weaker as the thermocline becomes weaker in the fall. Between the 1 st of July and mid-october, there is a tendency towards the local decreases in the area of oxygen deficiency occurring simultaneously with high wind speeds. The decrease in the area of less serious oxygen deficiency is larger and happens earlier than the corresponding decreases of the area with more serious oxygen deficiency (Figure 7). This can be explained by the latter area developing deeper than the first area, and as such, the wind speed required to mix the water to this depth would be greater, which means that this area decreases less when the water is only partially vertically mixed. The connection between high wind and the area of oxygen deficiency is clearer in simulation a than in b. In the model, annual variations in oxygen consumption depend on temperature (Eq. 3 & 4), which has the effect that the results as the oxygen concentration at all stations decreases in correlation with the temperature (Figure 10 & Figure 11) and the area of oxygen deficiency in Figure 7 starts increasing from July, as the water s temperature is at its highest, and decreases as the temperature falls in October. The increased temperature during summer also enforces the stability of the pycnocline and thereby inhibits mixing. 5.2 In- and outflows High saline inflows from the Skagerrak can be traced as an increase in bottom salinity starting from station 1 in the north and moving southwards through the stations. Bottom salinity is pictured in Figure 13, and in this figure such a development can be followed twice during the year in both 23

26 simulations. The first one starts at station 1 in early March and continues down through the stations until the salinity at station 4 at the Darss Sill increases in mid-april. The other one starts in late October at station 1 and ends in mid-november at station 4. These inflows happen in both simulations, but in simulation b, the salinity at stations 3 and 4 is lower, so it cannot be concluded that more inflow occurs in simulation b. More inflow might occur however, but it could be masked by a lower bottom salinity caused by increased vertical mixing. Increased salinity is not always related to increased oxygen concentration, but at some locations like in the deep part of the Kattegat (station 1), increased oxygen concentrations must be due to inflowing Skagerrak water. At the other stations, the oxygen concentration of the inflowing water will depend less on the properties of the Skagerrak water and more on the changes that occur in the straits when flowing from north to south. This is illustrated in Figure 11 where an increase in bottom oxygen concentration occurs at station 1 and 2 March simultaneously with the first inflow mentioned above, but at station 3 and 4, the inflow brings water with a lower oxygen concentration than the water already present at the stations, leading to a decrease in the oxygen concentration in conjunction with the inflow. The changes in mean salinity shown in Figure 14 give an idea of the water movement at the stations; an increase in mean salinity shows that inflow of high saline water dominates and a decrease means that outflow of low saline Baltic water dominates. The overall yearly mean of the salinity is slightly higher for simulation a than b, with the difference increasing from 0.8 % at station 1 to 5.9 % at station 3. The fact that the largest difference of mean salinity occurs in the Great Belt shows that the horizontal salinity gradient that exists in the Danish straits between the high saline Skagerrak water and the low saline Baltic water must have moved northwards, indicating increased outflow from the Baltic or decreased inflow from the Skagerrak. A possible explanation to the movement of the front is that the high wind speeds in January cause a larger high-saline bottom inflow to the Baltic in simulation b than in a, which in turn leads to a subsequent larger outflow of low-saline surface water and a northward movement of the front. Generally the fluctuations in mean salinity are higher in simulation b, indicating that wind driven movement of the water is increased, something that again improves oxygen concentration in the water. 5.3 Station 1 and 2 In simulation a, less oxygen deficiency occurs at station 1 than at the other stations (Figure 9). As already explained, part of the explanation can be a larger inflow of oxygen-rich water at this station, but the depth of the water below the pycnocline probably also plays a role as a deeper bottom layer means that a larger oxygen pool is available for each square meter of bottom, leading to oxygen deficiency occurring later than what would be the case with a more shallow bottom layer. Stratification probably also plays an important role at station 2 where the shallower water at this station means that a smaller oxygen pool is available here for each square meter of bottom. The inflowing water from the north presumably contains less oxygen here than at station 1, as oxygen is used on the way to station 2 and only little mixing occurs across the halocline, and this leads to oxygen deficiency developing earlier and the oxygen concentration becoming lower at this station as compared to station 1 (Figure 9 and Figure 11). This is also evident in simulation b where station 2 is the only station at which the bottom oxygen concentration falls below 126 mmol/m 3. Station 1 and 2 are probably re-oxygenated by similar mechanisms in the autumn. At station 1, re-oxygenation occurs between the 19 th and the 23 rd of October in simulation a, and between the 7 th and the 21 st of October in simulation b, and both of these increases occur at the same time as an 24

27 increase in salinity occurs ( Figure 15). This increase in salinity indicates that an inflow of high saline bottom water from the Skagerrak is partly responsible for the re-oxygenation at the station. An inflow would also be expected to increase the salinity difference between the bottom and surface water, thereby increasing the strength of the pycnocline, something that to some degree occurs (Figure 17). The reason that the strengthening of the pycnocline is not more obvious is probably that wind speeds higher than 13.6 m/s happen simultaneously with the increase in bottom oxygen concentrations in both simulations, mixing the water and thereby creating a smaller density gradient through the water column. The inflow and the following strengthening of the pycnocline explain why the oxygen concentration in both simulations does not increase on the 25 th to 29 th when wind speed comes above 16 m/s and vertical mixing could be expected to occur. And the lack of inflow explains why no increase in oxygen concentration occurs on the 1 st of October when wind speeds are also high and no inflow occurs. 5.4 Station 3 and 4 The location of station 3 in the Great Belt means that it is affected by the strengthening of the currents that occur when the water flow between the Baltic and the Skagerrak passes through the narrow Belt. This, along with increased friction from the bottom and the sides increases turbulence in the Belt and consequently conditions are more changing at this station as compared to the Kattegat stations (Leppäranta and Myrberg, 2009). But still, a halocline is in place at station 3 from March in both simulations (Figure 12e + f). The saline inflow that occurs at this time (Figure 13) is probably the initiation factor for the onset of the halocline, as the bottom salinity stays high after this inflow, leading to less vertical mixing until the autumn. Also, the onset of the halocline coincides with the earlier mentioned decrease in oxygen concentration, which can thereby be explained by both advection and less vertical mixing. Between the 1 st of October and 31 st of December bottom salinity and oxygen concentration have opposite gradients in the two simulations (Figure 18). In simulation b the salinity is lower and oxygen concentrations higher than in a, and together this indicates that saline inflows are not responsible for increased oxygen concentration at this station. On the other hand, decreasing bottom salinity indicates vertical mixing, which also explains the higher oxygen concentration, and as increased wind should increase vertical mixing, the lower bottom salinity and higher oxygen concentration in simulation b is also explained by this. Increased oxygen concentration coincides with low values for the strength of the pycnocline in both simulations (Figure 17) and increases in oxygen is connected to wind speeds higher than 11 m/s in simulation a, and in simulation b higher than 12 m/s, but wind speeds higher than this do not necessarily result in higher bottom oxygen concentration (Figure 16). This shows, that even though the increased wind in simulation b leads to higher oxygen concentrations in the water, there is no direct relationship between wind speed and increased 25