Simulated halocline variability in the Baltic Sea and its impact on hypoxia during

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1 JOURNAL OF GEOPHYSICAL RESEARCH: OCEANS, VOL. 118, , doi: /2013jc009192, 2013 Simulated halocline variability in the Baltic Sea and its impact on hypoxia during Germo V ali, 1,2 H. E. Markus Meier, 1 and J uri Elken 2 Received 10 June 2013; revised 14 October 2013; accepted 25 November 2013; published 18 December [1] Salinity and halocline depth variations in the Baltic Sea during are studied using a three-dimensional ocean circulation model. Significant interannual and interdecadal variations in the halocline depth are found, together with distinct periods characterized either by shallow ( ) or deep halocline ( ). The model simulation indicates that the mean top layer salinity in the Baltic Sea is mainly controlled by the accumulated river runoff, while the mean below halocline salinity in the Baltic proper (which comprises Bornholm and Gotland basins) is more dependent on the low-pass filtered zonal wind stress, with cutoff period of 4 years, henceforth called the mean zonal wind stress. The halocline depth and stratification strength in the Baltic Sea are significantly affected by the mean zonal wind stress, while the impact of runoff is smaller. The ventilation of the halocline from bottom layers is stronger during the shallow and from surface layers during the deep halocline period. Due to changes in ventilation variations in halocline depth systematically affect bottom oxygen concentrations on seasonal and decadal, but not on interannual time scales. For instance, a deeper halocline reduces hypoxic (oxygen concentration in bottom water below 2 ml/l) and anoxic (anoxic conditions in bottom water) areas and increases the bottom oxygen concentrations in the Gulf of Finland but decreases them in the deeper parts of the Baltic proper. Model results suggest that due to undersampling during mean hypoxic and anoxic areas calculated from observed profiles are underestimated by 41% and 43%, respectively. Citation: V ali, G., H. E. M. Meier, and J. Elken (2013), Simulated halocline variability in the Baltic Sea and its impact on hypoxia during , J. Geophys. Res. Oceans, 118, , doi: /2013jc Introduction [2] The Baltic Sea is a relatively small brackish sea located in northern Europe (Figure 1), with an estuarine circulation characterized by (a) water exchange through the Danish straits, (b) elongated multibasin bottom topography and coastline (Figure 1), (c) river discharge, and (d) atmosphere-ice-ocean interaction [e.g., M alkki and Tamsalu, 1985]. Sea dynamics is also strongly affected by sea ice covering during severe winters the entire sea area [Omstedt et al., 2004]. As typical for estuaries, net freshwater import from rivers combined with precipitation minus evaporation (on the average <15% from river discharge) are balanced by saline water import from the North Sea. Hence the brackish water export, resulting in a low 1 Department of Research and Development, Swedish Meteorological and Hydrological Institute, Norrköping, Sweden. 2 Marine Systems Institute, Tallinn University of Technology, Tallinn, Estonia. Corresponding author: G. V ali, Department of Research and Development, Swedish Meteorological and Hydrological Institute, Norrköping, Sweden. (germo.vali@msi.ttu.ee) American Geophysical Union. All Rights Reserved /13/ /2013JC mean salinity ( g/kg) compared to the adjacent North Sea, matches salt water inflows. [3] Spatial salinity variations are quite high. Typical estuarine gradients are present in the upper layers but the central part of the sea (named as Baltic proper) has also a persistent strong salinity stratification: halocline lies in about m depth and deep salinities range up to 14 g/kg in the Gotland Deep [Matth aus, 1984]. Long-term variations in river runoff and wind field over the Baltic Sea create significant changes in the salinity as shown by sensitivity studies. Meier and Kauker [2003a,b] and Meier et al. [2003] performed several experiments with the high-resolution three-dimensional Rossby Centre Ocean model (RCO) while others used either prognostic box models with vertical resolution [Omstedt and Axell, 1998, 2003] or diagnostic box models based on hydrographic observations [Winsor et al., 2001; Rodhe and Winsor, 2002]. Salinity response to changes in river runoff is rather slow (freshwater residence time is about 35 years), while reaction to changes in wind fields or sea level in the Kattegat is much faster [Meier, 2005]. The shortest forcing time scale is about a few days/weeks [Kauker and Meier, 2003]: sporadic major Baltic inflows create abrupt changes in halocline depth and deep salinity [Matth aus and Franck, 1992; Fischer and Matth aus, 1996; Lass et al., 2003]. 6982

2 ET AL.: SIMULATED HALOCLINE VARIABILITY IN THE BALTIC SEA VALI o 66 N BotB o 64 N o 62 N BotS Norway Finland 60oN BY31 58oN WGB GF BY27 NGB Sweden Estonia GR BY15 T2 EGB Latvia Stolpe Channel o 56 N Denmark AB BY5 BB GdB T3 T1 54oN o 12 E o o 16 E 20 E o 24 E o 28 E Figure 1. Topography of the Baltic Sea and locations of monitoring stations and hydrographic transects used in this study. Different regions in the Baltic Sea: AB 5 Arkona Basin, BB 5 Bornholm Basin, GdB 5 Gdansk Basin, EGB 5 Eastern Gotland Basin, WGB 5 Western Gotland Basin, NGB 5 Northern Gotland Basin, GR 5 Gulf of Riga, GF 5 Gulf of Finland, BotS 5 Bothnian Sea, BotB 5 Bothnian Bay. [4] The large interannual salinity variations in the Baltic Sea have been well documented on the basis of hydrographic observations at selected monitoring stations and reproduced earlier by model simulations [e.g., Elken et al., 2006; Fonselius and Valderrama, 2003; Lehmann and Hinrichsen, 2002; Meier and Kauker, 2003a; Meier, 2007]. The large variability of the total volume transport through the eastern Gotland Basin, which is the amount of water entering to the northern parts of the sea, has been shown earlier with different model simulations. Salt water inflows and total volume transports from RCO were analyzed by Meier and Kauker [2003a] and Meier [2007], while another three-dimensional coupled ice-ocean model was used to calculate volume, heat, and salt flux on eddypermitting scales by Lehmann and Hinrichsen [2002]. Nevertheless, the variability of the halocline along with the deepwater transport has not been studied before. Although the Baltic Sea is relatively shallow, the intermediate and bottom layers are isolated from the surface layers by a permanent halocline and a seasonal thermocline. Renewal of these water masses occurs by means of lateral advection from upstream basins. The bottommost layers are renewed only during major inflow events, while intermediate layers are ventilated by frequently occurring, smaller inflows. The volume transport into intermediate layers is considered as the halocline ventilation. [5] At least two exceptionally long stagnation periods, i.e., a period with reduced saltwater inflows from the North Sea characterized with strong decrease in the oxygen concentrations and salinity in low layers (during 1920s and 1980s) and similarly periods with very high salinity (in , , and in the late 1970s/early 1980s) were found during the last century [see Meier and Kauker, 2003a, Figure 8]. However, the impacts of low or high 6983

3 salinities in the Baltic proper on different physical properties of the overall Baltic Sea (volume transports, freshwater distribution, halocline ventilation, etc.) are yet not fully understood. In addition, little is known about the ecological impacts of reducing salinity in the Baltic proper (which comprises Bornholm and Gotland basins) and Baltic Sea in general. The surface salinity in the northern Baltic proper is close to the so called horohalinicum a critical range of salinities between 5 and 7 g/kg with the lowest number of species [Telesh and Khlebovich, 2010]. A decrease of salinity toward the horohalinicum will produce a shift in biodiversity and species composition. [6] Another often used indicator for ecosystem health in the Baltic Sea is the bottom oxygen concentration [HEL- COM, 2013]. Due to limited water renewal in the bottom, anoxic (no oxygen) and hypoxic (oxygen <2 ml/l) conditions appear in the deep areas of the Baltic Sea [Laine et al., 2007; Zillen et al., 2008; Conley et al., 2009], with large interannual variability [Hansson et al., 2011]. In this paper, we analyze the variability of the permanent halocline depth and stratification strength in the Baltic Sea simulated with a three-dimensional ocean circulation model. In addition, we investigate the impact of different forcing on the halocline depth, stratification strength, halocline ventilation, and anoxic and hypoxic areas. [7] The outline of this paper is as follows. In section 2, we give an overview of the model and methods used. In section 3, we analyze the variability of Baltic salinity, halocline depth and bottom oxygen concentrations and discuss the impact of different parameters on them. A summary and conclusions are given in section Material and Methods 2.1. Model Setup Physical Model [8] We use the three-dimensional Rossby Centre Ocean model (RCO) that has been previously applied for various ocean and climate studies [e.g., Meier, 2002a,b; Meier and Kauker, 2003a,b; Meier et al., 2004] and is described more detailed in Meier [2001], Meier et al. [2003], and Meier [2007]. [9] The ocean model is a regionalized version of the Ocean Circulation Climate Advanced Model (OCCAM) [Webb et al., 1997] coupled to a Hibler-type sea ice model and the subgrid-scale mixing in the ocean model is parameterized using a k-e type turbulence closure scheme with flux boundary conditions [Meier, 2001]. The deepwater mixing is assumed to be inversely proportional to the Brunt-V ais al a frequency with a proportionality factor a m 2 s 22, which is in good agreement with observations in the eastern Gotland Basin [Lass et al., 2003]. A flux-corrected, monotonicity preserving transport (FCT) scheme (as suggested by Gerdes et al. [1991]) is embedded without explicit horizontal diffusion. The barotropic and baroclinic modes in the model are separated with time steps of 15 and 150 s, respectively. [10] The model domain is based on the topography taken from Seifert and Kayser [1995] and covers the Baltic Sea with a horizontal resolution of about 3.8 km (2 nautical miles) and with 83 equally spaced vertical layers, whereas the layer thicknesses are 3 m. In the northern Kattegat an open lateral boundary is used, where in case of inflow temperature and salinity values are nudged toward observed climatological profiles in the southern Skagerrak and in case of outflow a modified Orlanski radiation condition is used [Stevens, 1991]. The sea level elevation at the boundaries is taken from daily tide gauge data. The simulation of gravity driven dense bottom flow is improved by embedding a BBL model to allow the direct communication between bottom boxes and step-like topography [Beckmann and Döscher, 1997]. [11] River runoff data are taken from Bergström and Carlsson [1994] and updated with results from a largescale hydrological model [Graham, 2004]. The atmospheric conditions for surface boundary are taken from the Rossby Centre Regional Atmosphere model (RCA) with a horizontal resolution of 25 km [Samuelsson et al., 2011; Meier et al., 2011]. The lateral boundary conditions for the atmospheric model are taken from ERA-40 reanalysis data [Uppala et al., 2005] updated with operational ECMWF data. This data set allows for hindcast simulations covering the period In previous studies, the atmospheric model RCA has been used successfully as boundary condition for the ocean model RCO [e.g., Döscher et al., 2002] Biogeochemical Model [12] RCO is coupled to the biogeochemical model SCOBI (Swedish Coastal and Ocean Biogeochemical model). SCOBI describes the dynamics of dissolved inorganic nitrogen and dissolved inorganic phosphorus, and particulate organic nitrogen and phosphorus that include phytoplankton, zooplankton, and detritus. The nitrogen and phosphorus content of organic matter is described by the Redfield molar ratio (C:N:P 5 106:16:1). Oxygen dynamics are included and hydrogen sulfide concentrations are represented by negative oxygen concentration, with equivalents 1 ml 522 ml. Phytoplankton consists of three functional groups representing diatoms, flagellates and others, and cyanobacteria. The latter group has the ability to fix molecular nitrogen. Organic matter sinks and enters the sediment containing benthic nitrogen and phosphorus. The sediment processes include oxygen-dependent nutrient regeneration and denitrification as well as burial of nutrients. Burial of nitrogen and phosphorus in the sediment and denitrification are the permanent nutrient sinks in the model. For further details, see Eilola et al. [2009, 2011, 2012] and Almroth-Rossell et al. [2011] Halocline Depth and Stratification Strength [13] We use the maximum vertical gradient criterion for definition of the halocline depth, as frequently adopted in the studies of coastal oceans [e.g., Kim et al., 2007]. Several open ocean studies use individual isopycnal levels to define the pycnocline depths; however, in the Baltic this approach is not favorable since the levels perform large vertical excursions over time and space and may occur in different vertical gradient zones. Being interested in longterm and seasonal halocline dynamics, the disturbing effect of high-range halocline variations due to mesoscale eddies [Elken et al., 2006] can be effectively suppressed by analyzing the monthly mean oceanographic fields. [14] Halocline depth H halocline ðx; yþ is defined as the location of the maximum of the first vertical derivative of the salinity: 6984

4 distance between these grid cells Dz. Therefore, halocline depth has discrete values defined by the grid configuration both of the observations and model results. [15] The mean vertical salinity gradient may have two maxima in the areas affected by runoff (Figure 2), where the upper one is due to the increased freshwater content in the surface layers (seasonal halocline) and the second is the perennial halocline (permanent halocline). In this study, we focus only on changes in the perennial halocline of the Baltic Sea and excluded the seasonal halocline. We follow the approach that the permanent halocline in the Baltic Sea is located deeper than 30 m and does not appear in areas with depths <50 m. [16] The stratification strength is defined as the difference between the bottom layer and top layer salinities. In this study, the top layer salinity is the mean volume weighted salinity in the range 0 60 m. The bottom layer salinity is the volume weighted average between 60 m and the bottom. The seasonality of the mean halocline depth and stratification strength is further analyzed as the difference between winter and summer values. Winter and summer are defined as the periods December to February (DJF) and June to August (JJA), respectively. Figure 2. Illustration of the method for detecting the halocline depth. Monthly mean salinity (blue lines) and vertical salinity gradient (black lines) in 1990 is shown for March (solid) and August (dashed) at lon 5 18E 57 0 and lat 5 58N The depths of the seasonal and permanent halocline are indicated with dashed lines along with the upper threshold for the halocline detection. DSðx; y; zþ H halocline ðx; yþ5h max (1) Dz where S(x,y,z) is the monthly mean salinity at the horizontal location x,y and the depth z(>0). The salinity gradient is calculated using the difference between the salinities in two vertically neighboring grid cells DS(x,y,z) divided by the 2.3. Observational Data [17] We used observed salinity and oxygen data for the model validation at four different monitoring stations (Figure 1) covering the period , extracted from the Baltic Environmental Database (BED) (Figure 3). The seasonal variations of oxygen concentrations were also validated along a transect T3 in Stolpe Channel. In addition, we also compared averaged observed and simulated surface salinity, bottom salinity, halocline depth, stratification strength, and bottom oxygen concentrations at different locations, where the number of observations was sufficiently large to allow a proper model evaluation. [18] All available measurements around the locations of the monitoring stations within a radius of 5 nautical miles were averaged in time over selected time periods at different depths. Correspondingly, all available measurements within a distance of 10 nautical miles to the T3 section were utilized. In order to allow a proper model-data comparison, the simulated profiles with 2 daily output were extracted and linearly interpolated to the time of observations from the nearest location. We use this method to cope with the difference in scales of the data coverage. The monitoring stations are usually covered by one measurement Figure 3. Number of observations (filled bars) and days with observations (hatched bars) at different monitoring stations of the Baltic Sea. 6985

5 Figure 4. (a) Inter-annual variability of annual mean runoff (blue thin line) with the corresponding 4 year running mean (blue bold line) and total accumulated runoff (black line). (b) Interannual variability of mean zonal wind stress (red) and wind curl (black). The dashed horizontal lines are the corresponding mean values of runoff, zonal wind stress and wind curl over the whole simulation period ( ). per month, which is not sufficient to make conclusions about monthly mean variability. Instead, the available data are averaged over some time period and the obtained datasets are compared to each other. [19] The number of observations available for different periods in the Baltic proper is largest at BY15, where we had >100,000 observations of salinity at different depths during distributed over 1835 different dates (Figure 3). The best temporal coverage of data is at BY5 with 1968 different days. The temporal coverage was lowest at BY32 with observations from only 542 different days. The number of observations (or days with available data) varied for and from 1100 (47) to 3582 (296) and from 4198 (57) to 23,969 (403), respectively. [20] The number of total observations along the transect T3 is larger for summer (JJA) with 47,529 observations than for winter (DJF) with only 29,882 observations. The number of days with observations along T3 during winter and summer is 682 and 470, respectively. [21] Overall, the number of available observational data is sufficient for the present study. A comparison between model results and observations at selected stations is given in section 3.1. In our study, we compare the time periods , , and These periods were selected to analyze the climatology of the halocline depth and stratification strength over (a) the whole simulation period , (b) a shallow halocline period , and (c) a deep halocline period Deep and shallow halocline periods were identified within this study (results presented in section 3.4) Forcing Variability [22] The main forcing factors controlling the Baltic Sea salinity and thereby the halocline depth are zonal wind speed and runoff [Meier and Kauker, 2003a,b; Kauker and Meier, 2003]. The impact of changes in river runoff to the Baltic Sea salinity is straightforward (more freshwater input reduces salinity), but understanding the impact of the wind field is more complicated. Meier and Kauker [2003a] were able to explain the wind effect on stagnation periods with decreased salt import from the Danish straits: increased westerlies create anomalous high sea level in the Baltic Sea and an additional barotropic pressure gradient along the straits, counteracting the salt import. [23] During the study period the mean annual runoff was approximately 15,330 m 3 /s with considerable interannual and interdecadal variability (Figure 4). A dry period with lower runoff occurred during and a wet period with larger runoff occurred during the stagnation period starting from the beginning of the 1980s to the mid- 1990s (values close to 16,000 m 3 /s). Runoff decreased rapidly again during the 2000s. The cumulative runoff anomaly, which integrates differences in runoff anomaly over time, varied between 250 and 100 km 3 during the 1960s, but decreased rapidly during to the minimum values close to 2400 km 3. During the stagnation period from 1980 to 2003 the runoff anomaly increased to the maximum value at 300 km 3. [24] The seasonal cycle of the runoff to the Baltic Sea is distinct (not shown). The largest values occur during March and the lowest values during the summer months with the minimum depending on the subbasin [Bergström and Carlsson, 1994]. [25] The monthly mean zonal wind stress and associated wind curl, averaged over the transect T2, had significant interdecadal variability (Figure 4) exhibiting, for instance, reduced westerly winds during and increased westerlies during This is in agreement with earlier specific studies [Alexandersson et al., 1998; Kauker and Meier, 2003; Lehmann et al., 2011]. The seasonal changes in wind stress are also considerable (not shown). The largest zonal wind stress with remarkably higher monthly mean values occurs during winter, while the zonal wind stress is lowest during summer. [26] To a large extent the changes in wind variability are explained by the variations of large-scale atmospheric circulation, identified by the NAO (North Atlantic Oscillation) index [Hurrell, 1995]. NAO has also significant impact on the variations in precipitation and runoff. Therefore, zonal wind and runoff are not independent forcing parameters Time-Series Analysis [27] Monthly mean distributions of the forcing and the oceanographic response fields contain a high degree of variance due to seasonal and year-to-year changes. Following Meier and Kauker [2003a], we analyzed low-pass filtered series with a cutoff period of 4 years to describe interdecadal variations. In particular, we studied top layer salinity (averaged between the sea surface and the halocline depth), salinity in the deep layer (averaged between the halocline depth and the sea bottom) and the halocline depth and 6986

6 Figure 5. (top) Observed (solid) and simulated (dashed) profiles of the mean salinity (bold line) and vertical salinity gradient (thin line) for different time periods and (bottom) observed (solid) and simulated (dashed) profiles of the mean oxygen concentration. Black, red, and blue lines describe the periods , , and , respectively. stratification strength. In order to quantitatively estimate the spatial impact of possible forcing parameters like accumulated runoff and zonal wind stress on the mean Baltic Sea salinity and halocline depth, we calculated the correlation between the low-pass filtered monthly mean values of a specific oceanic variable and the area-averaged forcing series at all grid points of the model domain. The results of the analysis are presented in section Transport Analysis [28] In order to study the ventilation of the Baltic proper by lateral currents carrying the transformed North Sea waters, we calculated the monthly cumulative volume transport through the Stolpe Channel and eastern Gotland Basin (transects T1 and T2, Figure 1). In earlier studies by Meier and Kauker [2003a] and Elken [1996], it was shown that there is a secondary maximum of the mean volume transports through the eastern Gotland Basin in depths of about m, whereas the largest transports occur in the upper layer due to the momentum input by the wind, i.e., the so-called Ekman transports. Transports in intermediate layers contribute significantly to the overall ventilation of the halocline in the Baltic proper Hypoxic and Anoxic Areas [29] Annual maximum hypoxic and anoxic areas were calculated from oxygen observations during autumn, when bottom oxygen concentrations are at its minimum. The hypoxic and anoxic depths obtained from the profiles were interpolated over the Baltic Sea area using the methodology from Hansson et al. [2011]. From model results hypoxic or anoxic areas were calculated either by (a) horizontally integrating the hypoxic or anoxic grid cells in space during each time step or by (b) averaging interpolated, simulated profiles at the locations (x,y,z) and dates of available observations following the procedure by Hansson et al. [2011]. The results are presented in section Results and Discussion 3.1. Comparison With Observations [30] At the different monitoring stations the model is able to reproduce both the climatological means and the temporal variations of selected, observed parameters, like salinity, halocline depth, stratification strength, and oxygen concentrations (Figures 5 and 6). In the Bornholm Basin (BY5) long-term mean salinity in the bottom layers is overestimated during the shallow halocline period, while the climatology and deep halocline period are very well captured. The halocline depth and mean vertical salinity gradient, which are controlled by salt water inflows from the North Sea and the deepwater flow across Stolpe Sill, are very well reproduced during all three periods and the long- 6987

7 Figure 6. Box and whisker plots of the difference between the annual mean simulated and observed surface salinity, bottom salinity, bottom oxygen concentration, halocline depth, and salinity difference at different monitoring stations of the Baltic Sea for the period term mean halocline appeared at 50 m both in observations and model results. Oxygen concentrations in the surface layer are well simulated, whereas bottom oxygen concentrations are slightly underestimated. [31] In the eastern Baltic proper (BY15) the simulated long-term mean salinity in the surface layers is slightly overestimated and the halocline depth is too shallow. In general, oxygen concentrations below the halocline are overestimated (except at the bottom during the deep halocline period). [32] Also in the northern Baltic proper (BY27) and western Gotland Basin (BY31) salinities in the bottom layers are overestimated and the vertical stratification is too strong, suggesting that in the model the vertical salt flux through the halocline is too weak compared to observations. At both stations oxygen concentrations in the water column below the halocline are underestimated during all periods, except in the western Baltic proper during the shallow halocline period. [33] The model tends to overestimate the mean vertical salinity gradient and to underestimate the halocline depth at almost all stations (except BY5) and during all periods. [34] The largest median difference between the annual mean simulated and observed surface salinity is <0.5 g/kg at BY5, while lowest discrepancies are found in the northernmost areas of the Baltic proper (Figure 6). Maximum surface salinity differences between model results and observations are smaller than 0.9 g/kg suggesting that in the model the short-term variability in salinity and related dynamics is relatively well captured. Median differences in bottom salinities are smaller than 0.3 g/kg. Largest discrepancies are found at BY31, where the model underestimates the salinity due to the truncated bathymetry (250 m compared to approximately 450 m in the observations). [35] Annual mean bottom oxygen concentrations are slightly underestimated in the model. The median differences are smaller than 0.4 ml/l. [36] At all stations, the annual mean halocline depths are under- and the stratification strengths are over estimated. Overall, the model performs well over the relatively long simulation period indicating that salt water inflows and mixing as well as biogeochemical cycles are simulated reasonably well Spatial Distribution Halocline Depth [37] The mean permanent halocline depth in the Baltic Sea during has significant spatial variability (Figure 7a). [38] In the Bornholm Basin, where the vicinity of the Danish straits causes large variations in salinity due to salt water inflows, the halocline is shallow, but it deepens toward the entrance of the Stolpe Channel, which prevents the inflowing saltwater to enter the eastern Gotland Basin. The halocline is relatively deep in the Stolpe Channel, Gdansk Bay, and even further in the entrance to the eastern Gotland Basin. In the central eastern Gotland Basin, a large-scale basin-wide cyclonic gyre produces a shallow halocline due to Ekman suction. This gyre has been noticed in earlier studies by Lehmann and Hinrichsen [2000] and Meier [2007]. [39] The halocline in the northern Baltic proper is located slightly deeper than in the central Baltic proper. In general, the deepest permanent haloclines in the Baltic Sea are found in the Gdansk Bay and northern Baltic proper, which contains the largest pool of juvenile freshwater [Hordoir and Meier, 2010]. [40] In the Gulf of Finland, the halocline depth is smaller in the eastern than in the western part. As there is no sill separating the Gulf of Finland from the rest of the Baltic Sea, the deep halocline from the northern Baltic proper simply stretches into the Gulf of Finland along the southern coast, while the halocline depth along the northern coast is shallower. [41] In the western Gotland Basin, the halocline becomes shallower compared to the northern Baltic proper with the deepest values occurring in the northwestern part of that subbasin. [42] In the figures, also the halocline depths in the Bothnian Sea and Bothnian Bay are depicted, but the vertical salinity gradients are small and the location of the maximum gradient is highly variable. Hence, we do not study the changes in the permanent halocline depth in these subbasins in details Stratification Strength [43] Also the salinity difference between the mean surface and bottom layers shows a significant spatial 6988

8 Figure 7. (a) Halocline depth in m and (b) stratification strength in g/kg in the Baltic Sea during Long-term mean observed values are shown with dots. variability (Figure 7b). The highest and lowest values are in the Bornholm Basin and in the gulfs, respectively. In the latter, the salinity is low and a permanent halocline does not exist, while in the first region salinity is largest compared to all other subbasins. The stratification strength becomes smaller through Stolpe Channel toward the Gdansk and eastern Gotland Basin. Slightly higher values remain in the central part of Gdansk Bay, while the stratification is relatively weak between the Gdansk Bay and eastern Gotland Basin. Interestingly, a larger vertical stratification is also found in the northern Baltic proper, which is caused by the large freshwater input and relatively large bottom depths. [44] In the model, the long-term mean stratification in the Gulf of Finland is overestimated, while in the northernmost areas (Bothnian Sea and Bothnian Bay) the stratification is slightly underestimated Seasonal Variability Halocline Depth [45] The seasonal cycle of the permanent halocline depth in the Baltic Sea is moderate (Figure 8a). The differences between climatological winter and summer mean halocline depths are <10 m in most of the Baltic Sea. The largest differences are found in the eastern Gotland Basin, where the large gyre is located and the winter halocline is lifted due to Ekman suction. In this area, the difference in halocline depth is even >10 m. The strong seasonal variations of the halocline between central eastern Gotland Basin and Gdansk Basin are also seen in the observations (Figure 8a). [46] In accordance to earlier results by Elken et al. [2006], differences in the permanent halocline depth during different seasons are also pronounced in the northern Baltic proper at the entrance to the Gulf of Finland, where the halocline in winter is deepest. An interesting feature is the difference in seasonal halocline depths along the Swedish east coast between winter and summer due to upwelling. Hordoir and Meier [2010] mentioned the impact of upwelling along the Swedish east coast on the distribution of the juvenile freshwater heights. [47] Simulated seasonal halocline variations are confirmed by long-term observations mean although observed seasonal variations in the Bornholm Basin are small (Figure 8a). In the southern and eastern Baltic proper the winter halocline in both observations and model results is shallower, while in the northern Baltic proper the halocline in winter is deeper than in summer Stratification Strength [48] The vertical salinity difference has a well pronounced seasonal cycle similarly to the halocline depth in areas affected by either river runoff or Ekman pumping/ suction (Figure 8b). In general, the strongest stratification occurs during summer and autumn, while the weakest stratification is found during winter and spring. [49] The largest seasonal changes in the stratification strength occur in the northern Baltic proper and Gulf of Finland. In these areas, seasonal variations in the stratification strength are larger than 0.7 g/kg, exceeding even 1 g/kg in the central Gulf of Finland both in simulations and observations. In the eastern Gotland Basin, the variations are at least two times lower according to the model simulations. However, in the Bornholm Basin the observed seasonality in stratification is not captured by the model. Nevertheless, in the outflow region of the Stolpe Channel the model is able to simulate a stronger stratification during winter, although the simulated stratification strength is slightly underestimated compared to the observations. [50] Mean correlations between seasonal variations in halocline depth and stratification strength are rather small in most areas of the Baltic proper and Gulf of Finland (not shown). Largest positive values are found in the saltwater outflow region of the Stolpe Channel, where the winter halocline is raised because of increased inflow activity in the Baltic Sea and stratification strength increased due to larger bottom salinity. Largest negative correlations are 6989

9 ET AL.: SIMULATED HALOCLINE VARIABILITY IN THE BALTIC SEA VALI Figure 8. (a) The difference between winter and summer halocline depth in m and (b) stratification strength in g/kg in the Baltic Sea during (c) The difference between winter and summer bottom oxygen concentrations, and (d) decadal variations in bottom oxygen concentrations in ml/l. Decadal variations are calculated as the differences between the and means. Longterm mean observed values are shown with dots. found in the western Gotland Basin, where the halocline is raised during summer due to the strong freshwater input, and stratification strength is increased due to the lower surface salinities Bottom Oxygen Concentration [51] Bottom oxygen concentrations show a pronounced seasonal cycle both in model simulations and observations. Absolute differences between the winter and summer concentrations exceed 2 ml/l (Figure 8c). The largest changes are in the shallow coastal areas of the Baltic Sea, where during winter the bottom oxygen concentrations are increased due to the larger impact of vertical mixing. [52] On the other hand, the seasonal cycle of bottom oxygen concentrations in the open sea is relatively small compared to the cycle in coastal areas. An exception is the narrow and relatively shallow Stolpe Channel, where bottom oxygen concentrations in winter are smaller compared to concentrations in summer as seen clearly at both sides of the channel. Seasonal changes of the halocline in the upstream basin, the Bornholm Basin, explain this unexpected result: during winter the halocline in the Bornholm Basin is shallow due to the inflowing salt-rich water from the North Sea and relatively oxygen-poor water from below the halocline ventilates the Stolpe Channel across the sill at its western entrance (Figure 9). To the contrary, during spring and summer the halocline in Bornholm Basin is deeper and relatively oxygen-rich water from above the halocline ventilates the Stolpe Channel during spring. Seasonal changes in the horizontal deep water flow through the channel during winter and spring are relatively small (not 6990

10 Figure 9. (left) Observed and (right) simulated oxygen concentrations at selected locations along the transect T3 through Stolpe Channel (see Figure 1) during (top) winter (DJF) and (bottom) summer (JJA). shown). This model result is confirmed by observations (Figure 9), although the feature is underestimated in the center of the channel. Notice that measured halocline depths along T3 during winter period are lower compared to the summer periods Interannual Variability Salinity [53] The Baltic Sea salinity changes considerably on decadal time scale as illustrated by horizontal maps of mean salinity averaged between the sea surface and the monthly mean halocline depth (top layer salinity) during and both in the model simulations and long-term mean observations (Figure 10). [54] The Baltic proper top layer salinity during was over 7 g/kg in most of the areas. In the southern Baltic proper simulated salinity exceeded 8.25 g/kg, whereas the long-term mean observed values were even larger. During the , the salinity in the Baltic proper had reduced significantly. The water with a mean top layer salinity >8.25 g/kg was pushed toward the Bornholm Basin. The top layer salinity in the western Gotland Basin and northern part of the eastern Gotland Basin had become <7.5 g/kg. Large changes were also found in the Gulf of Riga, where the salinity reduced from >6 to <6 g/kg. [55] Changes in the mean below halocline salinity between the periods were pronounced in the southern parts of the Baltic Sea and Gulf of Finland (Figures 10c and 10d). In agreement with the evolution of the surface salinity, changes in the northern parts of the Baltic Sea were small. The decrease of the salinity was explained by increased runoff together with increased westerlies and reduced salt water inflows during the stagnation period [Meier and Kauker, 2003a]. 6991

11 ET AL.: SIMULATED HALOCLINE VARIABILITY IN THE BALTIC SEA VALI Figure 10. The mean (a, b) upper and (c, d) bottom layer salinity, (e, f) halocline depth and (g, h) stratification strength in the Baltic Sea during (a, c, e, g) and (b, d, f, h) Observed mean values are shown with dots. 6992

12 Figure 11. Time-series of (left) simulated halocline depth and (right) stratification strength as vertical salinity difference at different monitoring stations of the Baltic Sea with annual mean observations (red dots). [56] The horizontal extent of the salinity change in the Baltic proper is remarkable. The surface salinity decreased into the critical range of the horohalinicum which might have an impact on the Baltic Sea ecosystem Halocline Depth [57] The annual mean halocline depths in the different parts of the Baltic proper have remarkable interannual variations (>30 m) both in observations and model simulations (Figures 10 and 11). In the Baltic proper also the lowpass filtered mean halocline depth with a cutoff period of 4 years shows significant changes during the simulation period (Figure 11). An exception is the Bornholm Basin (station BY5), where the low-pass filtered mean halocline depth remains close to 55 m and does not show any significant interannual variability, while the monthly variations were larger than 30 m. Obviously, the halocline depth is locked mainly by the depth of the sill at the western entrance to the Stolpe Channel which controls the downstream flow [e.g., Elken, 1996]. [58] The largest interannual variations were found in the northern and eastern parts of the Baltic proper, where the changes in the smoothed halocline depth exceed 20 m. In the eastern Gotland Basin (station BY15), the maximum change amounts to 18 m approximately. The shallowest halocline depths in the Baltic proper appeared during the 1960s and 1970s and the deepest during the 1990s (Figure 11). [59] The halocline depths during the shallow and deep periods are shown as the mean depths during and (Figures 10e and 10g). During , the halocline depth was larger in the southern Baltic proper (Gdansk Bay) and north-eastern part of the Baltic proper at the entrance to the Gulf of Finland. We found an especially shallow halocline in the eastern Gotland Basin and central Baltic proper, where the mean halocline depth was <59 m. During , the halocline depth in the Baltic proper was larger than 74 m in most areas. We found especially large halocline depths in the south-eastern part of Gdansk Bay and northern Baltic proper Stratification Strength [60] The vertical salinity difference also shows remarkable annual and interannual variations at all stations of the Baltic proper both in observations and model simulations (Figures 10 and 11). The stratification is stronger in the southern parts of the Baltic proper and smaller in the northern parts, while the month-to-month variations are largest in the northernmost parts of the Baltic proper. The weakest stratification occurred during the stagnation period in the southern and northern Baltic proper and is visible also in observations. [61] The differences in the stratification strength between shallow ( ) and deep ( ) halocline periods are shown in Figures 10g and 10h. During both periods the largest stratification is found in the Bornholm Basin and Stolpe Channel in the entrance to the eastern Baltic Sea. The decrease in the stratification strength between the shallow ( ) and deep ( ) halocline period is visible almost in all regions of the Baltic proper. An exception is the Bornholm Basin, where large inflows in 1993/ 1994 increased the stratification strength by at least 2 g/kg in the middle of the deep halocline period. In the other parts of the Baltic proper and Gulf of Finland, the decrease in stratification strength was at least 1 g/kg Bottom Oxygen Concentration [62] Decadal changes in bottom oxygen concentrations are even more pronounced compared to seasonal variations (Figure 8d). During the deep halocline period, the bottom oxygen concentrations in the deeper parts of the Baltic Sea are much lower compared to the shallow halocline period. The decrease in bottom oxygen concentrations is mainly explained by the reduced number of major Baltic saltwater inflows during the 1980s/1990s compared to the 1960s/ 6993

13 Figure 12. Correlations between annual mean surface salinity, bottom salinity, halocline depth and vertical salinity difference with mean zonal wind speed and total accumulated runoff at selected monitoring stations from observations (green bars), undersampled model results (blue bars) and annual mean model results (red bars). 1970s [e.g., Schinke and Matth aus, 1998]. However, during the deep halocline period an increase in bottom oxygen concentrations is found in the narrow transition zone in the Baltic proper between the coastal zone and the open sea (Figure 8b), where no vertical salinity gradient hampers the vertical ventilation of the sea bottom anymore. [63] In the Gulf of Finland, the increase in bottom oxygen concentrations during is explained by the stronger ventilation of the bottom layers due to increased westerlies. The increased zonal winds produce frequent upwelling along the northern coast of the Gulf of Finland causing an eastward geostrophic flow into the eastern Gulf of Finland [Zhurbas et al., 2008; Laanemets et al., 2011], which (a) ventilates the bottom with oxygen-rich water from intermediate layers and (b) lifts the halocline in the eastern parts of the Gulf Finland. However, as the halocline in the shallow eastern Gulf of Finland is strongly varying in time, decadal variations of the calculated halocline depth are statistically not defined. [64] In the next section, causes for the changes in salinity and halocline properties are quantified and discussed with respect to bottom oxygen concentrations Role of Drivers General Response [65] The main drivers controlling the salinity and thereby the halocline depth and stratification strength in the Baltic Sea are the runoff, wind field, and salt water inflows through the Danish straits into the Baltic proper. In this study, we investigate both observed and simulated correlations at different monitoring stations or at all model grid points between annual mean total accumulated runoff and zonal wind speed and salinity, halocline depth and stratification (Figures 12 14). Both annual mean surface and bottom salinities are inversely correlated with the annual mean zonal wind speed and accumulated river runoff (Figures 12 and 13). The largest correlations are found between runoff and surface salinity at all monitoring stations, while the impact of zonal wind is larger on bottom salinities in the central and northern parts of the Baltic proper. [66] The observed annual mean halocline depth at the monitoring stations shows low correlation with both the mean zonal wind speed and the total accumulated runoff, while the stratification strength is negatively correlated with the annual mean zonal wind speed (Figure 12). The impact of runoff is largest at BY5 and BY27. [67] The consequences of undersampling (due to the limited number of observations in time) for the estimated correlations are large (Figure 12). The correlations obtained directly from model simulations differ substantially from the correlations obtained from undersampled model results, while there are some discrepancies in correlations between model results and observations as well Regional Details [68] In the Baltic proper, top layer salinity and accumulated river runoff are correlated with remarkably high values, while the figures in the Gulf of Bothnia and Gulf of Finland are smaller (Figures 12 and 14). In the Bothnian Bay, the salinity response to changing runoff is faster and the correlations between salinity and the total runoff to the Baltic Sea are higher (not shown). The correlations between bottom salinity and total accumulated runoff are low in the southern Baltic proper. Relatively high values are found in the eastern and western Gotland Basin. These results indicate that the top layer salinity in the Baltic Sea is almost entirely controlled by the runoff, while the deep water salinity is also controlled by other forcing parameters like saltwater inflows into the southern Baltic Sea and zonal wind speeds. Indeed, in the southern Baltic Sea the correlation with the zonal wind stress is considerable. The high correlation between westerlies and deep layer salinity is seen also in other areas of the Baltic proper and Gulf of Finland. [69] On the other hand, the correlation between the top layer salinity and the westerlies is low in most areas of the Baltic Sea. Only in the easternmost parts of the Gulf of Finland correlations are significant as the increased westerly winds block the outflowing Neva river water and push them toward the southern coast due to the southward 6994

14 Figure 13. Correlations of the total accumulated runoff (a, b) and zonal wind stress (c, d) with the salinities averaged above the halocline (a, c) and below the halocline (b, d). Ekman transport. The westerly winds in the Gulf of Finland produce downwelling on the southern and upwelling along the northern coast, which promotes the southward Ekman transport. [70] In the Baltic proper, the correlation between the decadal variations of halocline depth and the accumulated total runoff is largest in the eastern Gotland Basin (Figure 14). However, correlations are small in the western Gotland Basin and in the Gulf of Finland. In these areas, the correlations with the westerlies are larger. Interestingly, in the central Gulf of Finland the impact of the coupled upwelling/downwelling effect on the halocline depth is clearly seen: in the southern (northern) Gulf of Finland, the halocline depth is increased (reduced) in case of increased westerly winds. In the eastern Gotland Basin, the lowest correlations with the westerly winds are found in the southern areas, where the basin-wide gyre controls the circulation. Obviously, the gyre is controlled by Ekman pumping and large-scale wind curl over the basin, which has different decadal variability compared to the westerly wind (Figure 3b). [71] The correlations between the total accumulated runoff or mean westerly wind stress and the stratification strength are stronger in the northern and western and weaker in the southern and eastern parts of the Baltic proper (Figure 14). The stratification strength in the southern areas is mainly dependent on the inflow activity and large correlations between saltwater inflows and stratification strength in the southern Baltic Sea are expected. In the northern and central areas of the Baltic proper the stratification strength is dependent more on westerly winds compared to runoff. [72] Changes in the Baltic halocline depth are negatively correlated with changes in the stratification strength (not 6995

15 ET AL.: SIMULATED HALOCLINE VARIABILITY IN THE BALTIC SEA VALI Figure 14. Correlations of the total accumulated runoff (a, b) and zonal wind stress (c, d) with the halocline depth (a, c) and stratification strength (b, d). shown). Deepening of the halocline is accompanied with reduced stratification strength Impact on Deep Water Ventilation and Oxygen Conditions Halocline Ventilation [73] Remarkable decadal variations in volume transports from the surface to the bottom are found at both studied transects (Figure 15). At the section across the Stolpe Channel (T1) largest transports occur at the surface and below the halocline in m of depth. Correspondingly, at the section across the eastern Gotland Basin (T2) we found largest transports at the surface between 0 and 50 m depth and in the range between 90 and 120 m depth. [74] The variability in the circulation above the halocline is to a great extent controlled by the wind field. During periods with increased wind curl, the volume transports in the surface layers are larger. The largest transports in the surface layers occurred during the late 1990s/early 2000s. [75] The mean volume transports during different periods differ significantly. During the shallow halocline period saltwater inflows through Stolpe Channel (section T1) are significantly larger than the transports during the deep halocline period. The stronger wind activity during the deep halocline period increases volume transports in the surface layer at T2. However, the maximum ventilation depth is not affected by changes in halocline depth and the corresponding transports in the depth range of the secondary maximum are only slightly lower during the deep compared to the shallow halocline period. [76] The impact of different forcing parameters on the halocline ventilation is summarized in Figure 16. The figures show the correlations between selected forcing series and the volume transports through transects T1 and T2 integrated between different depth ranges. 6996