Mean annual and seasonal circulation patterns and long-term variability of currents in the Baltic Sea

Journal of Marine Systems 193 (2019) 1–26

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Mean annual and seasonal circulation patterns and long-term variability of currents in the Baltic Sea

T

Jan Jędrasika, , Marek Kowalewskia,b ⁎

a b

Institute of Oceanography, University of Gdańsk, Al. Marszałka Piłsudskiego 46, 81-378 Gdynia, Poland Institute of Oceanology of Polish Academy of Sciences, Powstańców Warszawy 55, 81-712 Sopot, Poland

ARTICLE INFO

ABSTRACT

Keywords: Circulation pattern Hydrodynamic model Currents Baltic Sea

A hindcast modelling study conducted with the PM3D hydrodynamic model revealed some new effects. The study involved determination of seasonal characteristics of surface and subsurface currents. In addition, longterm relationships between the Baltic Sea currents and the North Atlantic Oscillation were explored. Analysis of the Baltic Sea current data spanning five decades has shown new, previously unknown, current characteristics, including higher stability (0.4–0.7) of subsurface current eddies relative to the stability of surface currents (0.2–0.5). Circulation anomaly patterns relative to the annual mean in spring and autumn present opposite flow directions, whereas winter and summer circulation patterns were similar in this respect. The spring circulation anomalies were dominated by the low sea-level outflow from the Baltic Sea, whereas the autumn circulation showed a strong inflow and infilling of the sea. In the analysed half-century (1958–2007), velocities of surface and bottom currents showed an increasing trend (0.9 and 0.1 cm s−1 per 50 years, respectively) and were related to the dominance of the positive NAO index phase. Current velocity fluctuations correlated positively with the NAO and BSI indices (correlation coefficients of 0.66 and 0.80, respectively).

1. Introduction Previous analyses of temporal and spatial current distribution patterns in the Baltic Sea were based on measurements carried out in the first half of the 20th century by Wittig and Palmen (Kullenberg, 1981) and Rudowitz (Jankowski, 1998) from lightships turned into research vessels. The paucity of the current flow rate data based on direct measurements contributed to the dynamic development of mathematical modelling of currents. The modelling studies addressed primarily the wind-driven currents (Kowalik, 1969, 1972, 1977; Jankowski, 1983a, 1983b; Andrejev and Sokolov, 1989). In the 1970s and 1980s, the circulation was analysed using 2D diagnostic (Sarkisjan et al., 1975; Kowalik and Staśkiewicz, 1976a, 1976b) and prognostic models (Kullas and Tamsalu, 1974; Tamsalu, 1980). In the following decades, 3D models came into use (Lehmann, 1995; Kowalewski, 1997; Lehmann and Hindrichsen, 2000a; Andrejev et al., 2004; Meier, 2007; Żurbas et al., 2011). Another problem addressed by circulation studies concerned density currents that were described with 2D models (Jankowski and Kowalik, 1980; Tamsalu, 1980; Stigebrandt, 1985, 1986). Of particular importance in this respect were the stratified water exchange in estuaries (Welander, 1974) and between the Baltic Sea and the North Sea (Kowalik and Staśkiewicz, 1976b; Chylicka, 1984; Chylicka and ⁎

Kowalik, 1984), as well as the exchange of salt and the outflow of brackish Baltic water to the North Sea (Svansson, 1980; Stigebrandt, 1987a, 1987b, 1993). Density currents were also studied in the context of oceanic inflows into the Baltic Sea (Herman and Jankowski, 2001; Andrejev et al., 2002; Meier and Kauker, 2002, 2003) and involved the determination of the water mass migration time (Döös et al., 2004; Andrejev et al., 2004; Meier, 2005, 2007). Another aspect of the Baltic Sea current research involved currents with a vertical component, i.e. upwellings (Kowalewski, 1999; Jankowski, 2002; Lehmann et al., 2002; Myrberg and Andrejev, 2003; Kowalewski, 2005; Kowalewski and Ostrowski, 2005; Lehman and Myrberg, 2008). According to Dietrich and Schott (1974), who published a synopsis of knowledge about the Baltic Sea currents, they can be regarded as weak, counter-clockwise and lacking any distinct pattern. Kullenberg (1981) in his monograph edited by Vopio gives a similar description and draws attention to a permanent cyclonic circulation. According to him, “the permanent circulation in the Baltic Sea is very weak and clearly associated with freshwater inflows; the current velocities are in the order of a few cm s−1 in the surface layer and somewhat less than 1 cm s−1 in the deep layers. The horizontal salinity distribution points to a cyclonic circulation, averaged over a long time period. The average circulation in the Gulf of Finland and the Gulf of Bothnia is cyclonic as well, with flow rates in the

Corresponding author. E-mail address: [email protected] (J. Jędrasik).

https://doi.org/10.1016/j.jmarsys.2018.12.011 Received 1 December 2017; Received in revised form 13 November 2018; Accepted 31 December 2018 Available online 22 January 2019 0924-7963/ © 2019 Elsevier B.V. All rights reserved.

Journal of Marine Systems 193 (2019) 1–26

J. Jędrasik, M. Kowalewski

order of 1 cm s−1. There is a single large eddy covering the surface of the Bothnian Sea, and another one covering the Bothnian Bay. The Coriolis effect on the circulation is considerable. The average movement in the surface layer is much more stable along the western than along the eastern shores due to combined effects of the river discharges and the Coriolis effect. The average circulation includes a weak vertical variability. Although storms in the Baltic are frequent and persistent, the mean winds are weak, the mean circulation in the Baltic proving to be mostly estuarine and thermohaline”. The paucity of reliable current measurements stimulated the development of models in the second half of the 20th century. The first study clarifying the modelled cyclonic circulation in the Baltic Sea was published by Sarkisjan et al. (1975). The model-based studies allowed determining circulation patterns in the Baltic as a result of exploration of hydrodynamic processes (Kowalik and Staśkiewicz, 1976a; Simons, 1978; Kielmann, 1981; Jankowski, 1983a, 1983b). The patterns depend on the model type. A solution for the Baltic circulation in relation to the scale of seasonal changes from April to November was presented by Jankowski (1998). He demonstrated that flow fields on a climatic scale are controlled by drivers, including baroclinic forces (generated by an inhomogeneous density field), bottom topography, and their interaction (Jankowski, 1998). Lehmann (1995) produced an averaged barotropic (vertically integrated) circulation model of the entire Baltic Sea based on simulations covering May and October of 1989–1993. He described the spring (May) water transport as baroclinic and circulation-driven, while the October transport as controlled by strong westerly winds. The pattern of the surface current field involved distinct cyclonic eddies in the Arkona, Bornholm, Gdańsk and Gotland Basins as well as in the Bothnian Sea (Lehmann, 1995). Based on simulations covering 1981–2004, Meier (2007) demonstrated the presence of strong and more stable cyclonic eddies in the surface circulation of the Baltic Proper and the Bothnian Sea, as well as the presence of cyclonic transport around the Gotland Deep and a south–west flow along the coast of Sweden as part of the cyclonic flow pattern in the Baltic Proper. Other studies (Lehmann, 1995; Meier, 2007) addressed long-term flows as well as flows associated with the North Atlantic Oscillation (NAO) (Lehmann et al., 2002). Elken and Matthäus (2008) presented a general scheme of large-scale circulation of waters in the Baltic Sea, both in the surface layer and in the bottom layer. Up- and downwellings occur along the shores and in the basin centres formed in cyclonic eddies as Ekman pumps. A decadal comparison of mean annual circulations showed that differences are very small. Each subbasin was characterised by cyclonic circulation (Lehmann et al., 2002). The present study aimed at analysing surface circulation patterns revealed by hindcast modelling, using a hydrodynamic model. The patterns are based on seasonal characteristics of surface and subsurface currents and long-term relationships between the Baltic Sea currents and the NAO. This paper is organised in five sections. This introduction is followed by the description of the M3D/PM3D hydrodynamic model developed at the Institute of Oceanography, University of Gdańsk. The section highlights the preconditions for the model's applicability to hindcast simulations covering 1958–2007 and describes the current method of field analysis. Results are presented as averaged vector fields of surface and subsurface currents, their stability as well as the magnitude of the currents' velocities. Subsequently, seasonal vector fields of currents, followed by a description of the long-term (five decades) current variability, focusing on the relationship with atmospheric activity as expressed by the NAO and BSI (Baltic Sea Index) indices. The fourth chapter compares the results obtained by current modelling with published evidence. The paper concludes with an overview of the results and an indication of new knowledge about the Baltic Sea currents gained through the described study.

University of Gdańsk (IOUG), the Leibniz-Institut für Ostseeforschung Warnemünde (IOW),1 the Gdynia Naval Hydrographic Office, and the Maritime Institute in Gdańsk (MIG). Data on the hourly weather conditions on the sea surface were obtained from the re-analysis of REMO for the period 1958–2001 provided by IOW and the Centre for Materials and Coastal Research (Helmholtz-Zentrum Geesthacht, HZG) for the period 2002–2007. Mean monthly discharges of 167 rivers into the Baltic Sea were used at the coastal borders. The relevant data for the period 1970–2007 were made available by the Baltic Environment Database of the Nest Institute (http://nest.su.se/bed/). Daily data from Polish rivers came from the Institute of Meteorology and Water Management (IMWM). Due to the lack of data for the period 1958–1969, average monthly river inflows for the decade 1970–1979 were used to fill this gap. The river inflow into the Baltic in individual years ranged from 356 to 596 km3; 497 km3 on average. For validation purposes, the modelled hydrodynamic parameters were compared with sea level data at coastal stations as well as with temperature and salinity records from buoys. These vertical temperature and salinity profiles obtained for validation were not averaged. The data collected at monitoring stations were provided by the International Council for the Exploration of the Sea (ICES), the Institute of Meteorology and Water Management, and the European Marine Observation and Data Network (EMODnet). Basic statistical metrics, e.g. the correlation coefficient (R), the systematic error (bias) and the root mean square error (RMSE) were used to explore the similarity between the modelled and observed variables. 2.1. Brief description of the M3D/PM3D model The circulation patterns were simulated by running the three-dimensional hydrodynamic model PM3D (Kowalewski and KowalewskaKalkowska, 2017), a new version of the M3D model (Kowalewski, 1997), which enables parallel numerical calculations. The model is based on the Princeton Ocean Model (POM) developed at Princeton University (Blumberg and Mellor, 1987). Like POM, the M3D/PM3D model uses the Mellor-Yamada turbulence scheme (Mellor and Yamada, 1982) and sigma vertical coordinates. However, the numerical scheme used to calculate the advection in M3D/PM3D differs from that used by POM. Due to the specific conditions of the Baltic Sea, adjustments to the original POM were needed to allow for its effective adaptation (for details see Kowalewski, 1997). One of the major modifications was introduced in the central difference scheme in advection transport equations. The conservative differential scheme ULTIMATE (Universal Limiter for Transient Interpolation Modelling of the Advective Transport Equations) based on the TVD (Total Variation Diminishing) filter (Leonard, 1991) was combined with the original POM central difference scheme, separately for each direction. As the ULTIMATE scheme provides the monotonicity of any one-dimensional explicit advection numerical scheme, the procedure prevents oscillations and local extremes from assuming unrealistic values (e.g. negative salinity) in the regions of steep salinity gradients. The nature of horizontal and vertical density distributions across the Baltic Sea and the adoption of the σcoordinate system implied the possibility of errors in the determination of density gradients (Haney, 1991) and horizontal diffusion. To minimise such errors, a subtraction of the area-averaged density was applied before the density gradient evaluation (Kowalewski, 1997). 2.2. Application of the PM3D model in long-term simulations In this study, the PM3D model was used to perform retrospective simulations of the hydrodynamics in the entire Baltic Sea with a horizontal 3 NM resolution. The vertical domain in the water column was assumed to be 18 σ-layers with thinner layers near the surface and

2. Materials and methods Bathymetric data used to construct a 3 nautical mile (NM) grid of the Baltic Sea were provided by the Institute of Oceanography,

1

2

See Seifert and Keiser (1995).

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J. Jędrasik, M. Kowalewski

bottom. The thickness of the surface and bottom layer was assumed to be 0.5% and 2% of the water depth at each node of the numerical grid, respectively, with the thickness in the middle of the profile amounting to 8.3%. An open boundary was located between the Skagerrak and the Kattegat along the parallel connecting Skagen and Göteborg, at the place where the water exchange with the North Sea takes place. The boundary condition was based on observations of the hourly sea-level fluctuations at the Göteborg station by the Swedish Meteorological and Hydrological Institute (SMHI). A radiation condition was applied (Hedley and Yau, 1988) based on Somerfield's concept for velocities (V), vertically averaged and normal to the boundary plane:

V=

C ( h

)

dropped to the freezing point, a boundary condition of no sea-atmosphere momentum and heat exchange on the surface was adopted, i.e. it was assumed that the wind stress and the net heat flux on the surface are equal to zero. Negative air temperatures over the ice, produced by the atmospheric model, kept the freezing temperature on the surface, which reduced wind stress on the sea surface. Such assumptions allowed accounting for, in a simplified manner, the presence of ice and its effect on energy exchange with the atmosphere. In addition, this assumption prevented water temperature from dropping below the freezing point. Runs of the hydrodynamic Baltic Sea model, performed for the period 1958–2007, produced daily surface, subsurface (20 m, 40 m and 60 m) and near-bottom current fields. They were used to calculate averaged currents with their stability and moduli on the climatic scale. To obtain the mean current field vector V for a given period, the u and v components were averaged (Neumann and Pierson, 1967):

(1)

where: C is the long-wave velocity, C = gh ; g is the gravitational acceleration on Earth, h is depth; η is the free surface elevation defined as the mean of the surface elevation values for grid points on the open boundary calculated based on the continuity equation; η′ is the free surface elevation observed in the vicinity of the open boundary.

u=

1 N

N

ui ,

v =

i=1

1 N

N

vi i=1

(2)

The mean current moduli were averaged as follows:

V =

The approach applied resulted in the smallest reflection effects. The water surface elevation η in the context of wind-driven circulation did not incorporate the short-term wind wave motion and was considered as the mean sea surface elevation, i.e. the time averaged over many wind wave periods. The salinity of water entering the Baltic Sea via the open boundary was adopted based on monthly mean vertical distributions, as determined by measurements along vertical profiles taken during research cruises in 1969–2007 in the area of the Skagerrak-Kattegat border; the data are stored in the Baltic Environment Database of the Nest Institute. The temperature of water entering the Baltic Sea was assumed to be identical to that in the Kattegat (assumption of the null gradient perpendicular to the boundary). Atmospheric forcing for the period 1958–2007 was performed using the regional atmospheric climate model REMO (REgionalMOdel; Jacob and Podzun, 1997), which was based on the numerical weather prediction model EM (Europa-Modell) of the German Weather Forecast Service (DWD). The surface boundary conditions for heat fluxes were described by bulk formulae analogous to those used in POM and parameterised according to the energy exchange across the sea surface through short- (Krężel, 1997) and long-wave radiation as well as the sensible and latent heat transfer (Jędrasik, 1997, subsequently revised by Herman et al., 2011). The input of the energy flux component due to a slight surplus of net precipitation, almost compensating for evaporation (127 mm year−1 during the last century, i.e. about 20%; Rutgersson et al., 2002), was omitted. Wind stress drag coefficients were parameterised according to Hellerman and Rosenstein (1983). Following the calibration of the model at the 3 NM grid, the drag coefficient was assumed to be 2.3 · 10−3. In winter, part of the Baltic Sea is usually covered with ice. The longest ice cover duration (up to 6 months) is observed in the northernmost part of the Gulf of Bothnia. Depending on the winter severity, the Gulfs of Finland and Riga may also be covered with ice. Depending on the ice concentration, the ice cover limits the transfer of momentum and heat from the atmosphere, which in turn affects the surface circulation. The model used did not include a sea ice module and thus could not fully account for ice conditions. However, the effects related to the presence of ice were partly included. The atmospheric forcing used was derived from the REMO model, which did account for the presence of sea ice and, should that occur, generated negative air temperatures. Such conditions resulted in cooling of the sea surface layer. When the sea surface temperature simulated by the PM3D model

1 N

N

ui2 + vi2 i=1

(3)

The current field vector stability S was determined (after Lehmann and Hindrichsen, 2000b) as follows:

u2 + v 2

S= 1 N

N i=1

ui2 + vi2

(4)

The current velocity fields were averaged over the entire simulation period as well as seasonally. Differences between the whole-period and seasonal fields were treated as seasonal variability anomalies. The obtained current pattern was compared with the results of other studies on the Baltic Sea current system. 2.3. Validation of the hydrodynamic model So far, the 5 NM-resolution M3D model has been subjected to comprehensive validation against long-term observations of the sea level, salinity and temperature. The results concerning the spatial and seasonal variability in shallow and deep coastal waters as well as in the open sea were presented in relation to the observed values (for details see Kowalewski, 2002; Kannen et al., 2004; Jędrasik, 2005; Jędrasik et al., 2008). The modelled sea surface temperature fields were also compared to those obtained from the appropriate satellite SST images (Jędrasik, 2005; Kowalewski et al., 2009). Prior to the research on storm surges, the PM3D version of the model with new bathymetric 3 NM grids was validated according to the water level variation (Kowalewski and Kowalewska-Kalkowska, 2017). In addition to taking into account the sea-level oscillations, the validation carried out in this study was extended to include temporal and spatial distributions of temperature and salinity affecting the Baltic hydrodynamics. Due to the scarcity of reliable current measurements, the validation was based on long-term, almost half-century, time series of observations of the abovementioned parameters. 2.3.1. Validation of the modelled sea-level variations Validation of the hydrodynamic PM3D model involved open sources and available observations from monitoring stations and tide gauges. A total of 15 sea level gauges were selected, distributed evenly around the Baltic Sea (Fig. 1). The observations involved different periods of measurements, ranging from 3 to 50 years (Table 1). The shortest periods concerned the eastern coast. Measurement series consisted of 15 to > 55,000 records, mostly with 1-hour resolution, but there were also 3

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Fig. 1. Location of the monitoring stations (stars) and tide gauges (circles) used for validation of the model results, in relation to the Baltic Sea bathymetry.

NAO index values as well as those for the atmospheric pressure at Oslo and Szczecin stations for the period 1958–2007 (available at the NOAA website https://www.esrl.noaa.gov/psd/) were used. Geodesic vertical reference systems (e.g. Kronsztadt, Amsterdam) differ between countries. The systems were also modified during the period covered by this study. Therefore, it is difficult to refer data from individual stations and from the model to a common reference level. To eliminate errors arising from referring the sea level to a common reference level during the validation, the differences between the observed and modelled mean sea levels were removed. These operations, carried out for each station, resulted in the elimination of the bias in the modelled sea levels. The quality of the sea-level variation simulation in the Baltic Sea over the half-century was determined (by omitting the biases) using correlation coefficients and RMSE. The correlation coefficients were high and ranged from 0.84 in Warnemünde to 0.95 in Visby; ten stations produced correlation coefficients of 0.9–0.95 (Table 1). The lowest RMSE (7.2 cm) was determined in Visby and the maximum (18.7 cm) in Skt. Petersburg (the Gulf of Finland). A comparison of the mean monthly sea levels at the Göteborg station with hourly observations (producing a condition on the open boundary of the model) and data calculated for Marviken (Fig. 2) showed a close agreement of the time courses. This was due to the fact that the sea level in Marviken was a good approximation of the mean sea level of the Baltic. This is associated with the degree of Baltic infilling which, on the monthly scale, is largely determined by the sea level in the Skagerrak due

Table 1 Statistics produced by comparing the modelled versus observed sea-level variations. Station

RMSE [cm]

R

Amount of data

Warnemunde Ustka

14.1 10.3

0.84 0.93

416,398 145,660

Gdańsk

10.0

0.93

123,666

Klaipeda Daugavgriva Tallinn Skt. Petersburg Helsinki Turku Vaasa Kalix Spikarna Marviken Ystad Visby

9.4 13.3 10.0 18.7 11.0 15.1 11.8 15.6 13.9 8.0 11.4 7.2

0.94 0.89 0.95 0.87 0.94 0.90 0.94 0.90 0.86 0.94 0.89 0.96

17,839 19,321 18,662 15,791 262,963 262,963 262,961 281,743 343,975 378,002 254,314 414,883

Observation period/ frequency 1958–2007/1h 1958–2006/4h 2007/1h 1958–2006/4h 2007/1h 2005–2007/1h 2005–2007/1h 2005–2007/1h 2005–2007/1h 1978–2007/1h 1978–2007/1h 1978–2007/1h 1974–2007/1h 1968–2007/1h 1964–2007/1h 1958–1987/1h 1960–2007/1h

4-hour intervals between the measurements. No averaging or filtering of observational data was applied during validation. In total, the study used more than three million data records. To determine the BSI, the 4

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Fig. 2. The time course of the mean monthly sea-level variations observed in Göteborg and modelled for Marviken in 2000–2007.

good fit with observations (Figs. A4, A5, A6). Salinity usually showed a low bias (from −0.55 to 0.19 PSU) and was mostly slightly underestimated (Table 3). Larger deviations were observed only in three cases (BY 70 m, BY38 80 m, LL7 50 m). On the surface, the RMSE ranged within 0.15–0.5 PSU. Larger errors (> 1 PSU) were obtained only at BY5 50–70 m and P1 100 m. The coefficients of correlation between the modelled and observed salinity ranged from 0.13 in the Gulf of Riga to 0.84 in the Bothnian Bay (Table 3). As opposed to the temperature, the coefficients did not always decrease with depth. At most stations, the highest values were associated with a depth of 50 m. In general, the PM3D captured fairly well the long-term (50 years) variability in the validated parameters and can be regarded as a reliable model to simulate the hydrodynamics of the Baltic Sea.

to the importance of the barotropic exchange in the sea-level variation in the Baltic (Kulikov et al., 2015). An indicator of interdependence between monthly sea-level means observed in Göteborg and sea levels modelled for Marviken for 50 years was the correlation coefficient of 0.74, which confirms the validity of the boundary condition on the open border of the model assumed in Göteborg. Error histograms were drawn for three stations: Kalix at the northern Baltic Sea coast, Visby in the central part and Ustka at the southern coast (Fig. 3). The error distribution is normal in each case. The smallest errors were in the central part of the Baltic Sea, while those in the northern part were the largest. 2.3.2. Validation of the modelled temperature and salinity distributions The modelled temperature and salinity distributions were validated for selected monitoring stations: BY5 in the Bornholm Deep; P1 in the Gdańsk Deep; BY15 and SR38 in the Eastern and Western Gotland Deep, respectively; 16 in the Gulf of Riga; LL7 in the Gulf of Finland; A13 in the Bothnian Bay; and SR5 in the Bothnian Sea (Fig. 1). Data records at six stations covered the whole period of five decades. The observations at LL7 and BY15 have started in 1959 and 1962, respectively. Station 16 in the Gulf of Riga produced the shortest time series (starting in 1986). Temperatures were validated at selected depths for individual stations (Table 2). The simulated versus observed temperature comparisons of the 50year time series at the stations located quasi-longitudinally, from A13 via BY15 to BY5, showed a very similar range of variation (−0.8 °C to 23 °C) (Figs. A1, A2, A3). A bias as a systematic error indicated that the modelled surface temperature was too low and ranged from −1 °C in the Gulf of Riga to −0.2 °C in the Gulf of Bothnia (Table 2). The statistical error expressed as RMSE ranged from 0.9 °C in the Bornholm Deep to 1.5 °C in the Gulf of Riga. The coefficients of correlation between the simulated and measured temperature ranged from 0.97 to 0.99 (Table 2). Very high correlation coefficients and low RMSEs indicate a good model performance in reproducing the observed sea surface temperature. As opposed to the surface temperature, the model overestimated the temperature at greater depths (40–100 m) by a maximum of 1.8 °C (A13, 40 m). The temperature at the deepest station (BY15, 150 m) was not biased, but the model indicated the presence of seasonal fluctuations, which are not present in the observations (Fig. A2c). As a result, the correlation coefficient was close to zero. At most stations, RMSE increased with depth, except for the Bothnian Bay stations (SR5 and A13), where RMSE decreased with depth. At a depth of 50 m, the correlation coefficients were relatively high, ranging from 0.54 to 0.74, which – along with a relatively small bias and low RMSE – proved the correct modelling of the subsurface layer. The low correlation coefficients (from −0.15 to 0.02, with exception SR5 station where R = 0.64) for the 100–150 m depth interval indicate a poor fit between the modelled and observed temperatures. Similarly to the temperature, simulations of salinity changes at A13 (the Bothnian Bay), BY15 (the Eastern Gotland Deep in the Baltic Proper) and BY5 (the Bornholm Deep in the southern Baltic) showed a

3. Results 3.1. Surface and subsurface currents The mean vectorial surface current field in the Baltic Sea, averaged over five decades, showed mostly cyclonic and anticyclonic circulation patterns and intensified flows (Fig. 4a). Intensified flows (inflows in the Kattegat) occurred in the southern Baltic, in the Gotland Basin (northeastwards in the Eastern Gotland Deep and southwards in the Western Gotland Deep) and in the Bothnian Sea. There were also cyclonic rotating structures with high stability up to 0.6 and horizontal cyclonic circulations in the Arkona, Bornholm and Gotland deeps. An anticyclonic flow was found north of the Słupsk Trough: the east-flowing surface currents were stable in the intermediate zone between the Bornholm and Gotland Basins. The eastward flow was confirmed to continue between the Gdańsk and Gotland Basins. The mean annual surface circulation could be characterised as flows of low stability. Distinct cyclonic eddies were observed at a depth of 20 m in the Baltic Proper and in individual basins. The averaged current field in the analysed period was characterised by the presence of a cyclonic vortex related to the bottom topography in the Arkona and Bornholm Basins, showing 0.6–0.7 stability and a clearly visible flow pattern affecting the water exchange through the Bornholm Gate (Fig. 4b). Another whirl was observed in the Eastern Gotland Basin; a fairly distinct NE–SW flow in the Western Gotland Basin was divided into two streams in a southerly direction, which merged in the Bornholm Basin. The subsurface, mostly cyclonic patterns were much more stable than those occurring in the surface circulation. The south-western current, from the Gulf of Finland to the northern shores of Oland in the western part of the Gotland Basin showed 0.5–0.7 stability. The eastern part of the Gotland Basin featured a cyclonic circulation of 0.3–0.6 stability. Two separate cyclonic circulations were found in the Bothnian Sea and the Bothnian Bay. The western branch of the Bothnian Sea cyclonic pattern was divided into two parts heading south. The Bothnian Bay also featured a cyclonic circulation pattern. Meridional current patterns were revealed, with currents meandering in relation to the bottom 5

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Fig. 3. Distribution of differences between the observed and simulated sea levels at stations Kalix (a), Visby (b), and Ustka (c).

topography and the configuration of the coast. Currents in other areas were characterised by low stability and velocities. In the southern Baltic basins, the subsurface currents were more stable than the surface currents (cf. Fig. 4a, b). Cyclonic circulations, found at a depth of 20 m, were also observed at 40 m (Fig. 4c) and 60 m (not shown), especially in the Bornholm and Gdańsk Deeps with water transported eastwards via the Słupsk Trough. The local rotary movement became pronounced at the same depths in the Gotland Basin. Eddies in the Bothnian Bay and the Bothnian Sea were reduced horizontally but were still stable (stability of 0.5 and 0.7 in the Bothnian Bay and the Bothnian Sea, respectively). As opposed to

the surface currents in the Kattegat and Oresund, the bottom currents (Fig. 4d) followed the North Sea inflows. Subsequently, stronger bottom currents occurred at the entrance to the Bornholm Basin, in the Słupsk Trough, in the Sea of Åland and in the eastern part of the Bothnian Sea. Average surface current velocities were spatially differentiated. Areas with intense flows occurred in two types of elongated belts, one with a meridional direction and the other with a (zonal) latitudinal course (Fig. 5a). The meridian belt ran along the east coast of the Baltic Sea from the shores of Latvia to the Gulf of Bothnia, and a much shorter section was located south of Gotland. The zone of intense flows with a latitudinal (zonal) flow pattern was observed along the coasts of 6

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the Sea of Åland (Fig. 5b). Currents at a depth of 40 m were locally separated. Flows in the Baltic Proper were present in all connected deeps and the Gulf of Finland. The Bothnian Bay, the Gulf of Riga and the Bothnian Sea showed local fields of separate flows, not connected at that depth with the circulation in other areas due to the bathymetry. The magnitude of the current velocity covered the range of 0.04–0.1 m s−1, with the dominance of 0.06–0.8 m s−1 (Fig. 5c). The most intense flows at a depth of 40 m were observed in the Słupsk Trough. The bottom currents showed the lowest values (lower than 0.06 m s−1), with the dominance of 0.03 m s−1 (Fig. 5d).

Table 2 Statistical indicators of differences between the modelled and observed sea surface temperature in the Baltic Sea over the period 1958–2007. Station BY5 BY38 BY15

P1 SR5 A13 LL7 16

Depth [m]

Bias [°C]

RMSE [°C]

0 50 70 0 50 80 0 50 100 150 0 50 100 0 50 100 0 50 90 0 50 0 40

−0.64 0.77 0.54 −0.73 0.33 0.46 −0.66 0.48 0.33 0.00 −0.67 0.81 0.24 −0.23 0.56 0.25 −0.26 0.84 1.31 −0.62 0.59 −1.03 1.83

0.92 1.61 1.77 1.09 1.18 1.26 1.07 1.35 1.17 0.94 1.03 2.43 2.33 1.04 1.01 0.79 1.21 1.04 1.04 1.26 1.87 1.47 2.18

R 0.99 0.73 0.46 0.98 0.74 0.25 0.98 0.70 −0.06 0.02 0.99 0.66 −0.15 0.98 0.74 0.64 0.97 0.72 0.62 0.98 0.54 0.97 0.70

Number of records 1052 1092 1039 546 561 559 852 831 925 807 973 973 835 349 319 337 365 202 195 573 564 212 201

Observation period 1958–2007 1958–2007 1962–2007

3.2. Seasonal variability of circulation The winter circulation was characterised by cyclonic patterns similar to those visible in the annual averages. However, the vortices were different in the Bothnian Sea and in the Baltic Proper between the Gotland Sea and the Åland Sea. Areas with higher stability (0.35–0.5) included the Bornholm and Gdańsk basins, the basins west and east of Gotland, as well as the flows between the Gulf of Bothnia and the Baltic Proper (Fig. 6a). In spring, the currents were weaker and less stable. The rotary movements in the northern part of the Baltic Sea, particularly in the Bothnian Bay and the Bothnian Sea, were also clearly reduced. In the Gulf of Finland, the currents were observed along the southern coast as eastern flows and along the northern coast as western flows with stabilities of 0.4 and 0.2, respectively. In the northern part of the Baltic Proper, the current flow was divided into branches directed to the basins east and west of the Gotland Basin (Fig. 6b). The summer circulation pattern showed intensified flows in the southern part, with a distinct component of eastern flows and stability of 0.3–0.45. Cyclonic circulation patterns occurred in the Bothnian Sea as well as in the Bornholm and Arkona basins (Fig. 6c). The autumn circulation preserved the eastern component of the surface current, with stability higher than that in summer (0.3–0.5). Eddies were observed in the Bothnian Sea and the Bothnian Bay; the exchange between these areas as well as between the Gotland Basin and the Åland Sea intensified. The Arkona and Bornholm basin vortices, showing traits of cyclonic flows in the earlier seasons, became less distinct in autumn (Fig. 6d). The surface currents were mainly driven by atmospheric effects. The average monthly wind velocity fields indicated that for four decades the velocities were increasing from May to November and decreasing from November to May. The lowest velocities were observed in spring (April, May, June); the wind directions were also the least stable at that time (Jędrasik, 2014). The magnitude of the surface current velocity fields (Fig. 7b, c) confirmed the highest flow intensity in summer relative to spring. The averaged seasonal flows at the four selected depths (0, 20, 40 m and near the bottom; Table 4) showed that the lowest values are typical of spring. The velocity field in winter proved similar to the field of the mean annual magnitudes of the current velocity (cf. Figs. 5a and 7a). The moduli of surface currents in spring were lower than the winter field currents by 0.1 m s−1. Areas with currents of 0.10–0.15 m s−1 velocities became more extensive (Fig. 7b). The current field in summer was most homogenous in terms of the magnitude of the current velocity, ranging from 0.10 to 0.25 m s−1 (Fig. 7c). Values higher by 0.05 m s−1 occurred in the autumn field (Fig. 7d). The mean magnitude of the current velocity in the central parts of the Baltic Sea ranged from 0.1 to 0.2 m s−1, while those off the eastern and southern coasts reached the values of 0.4 m s−1. The magnitudes of the current velocity in the autumn significantly affected the field of annual mean values. The basic features of the flows included the intensification along the eastern coast and south of Gotland as well as a latitudinal belt along the German and Polish coast, forming an area featuring currents of higher velocities; the remaining extensive areas showed weaker currents. The lowest magnitude of the current velocity occurred in the Gulfs of Gdańsk, Riga,

1958–2007 1958–2007 1958–2007 1959–2007 1986–2007

Table 3 Statistical indicators of differences between the modelled and observed seawater salinity in the Baltic Sea for the period 1958–2007. Station BY5 BY38 BY15

P1 SR5 A13 LL7 16

Depth [m]

Bias [PSU]

0 50 70 0 50 80 0 50 100 150 0 50 100 0 50 100 0 50 90 0 50 0 40

−0.02 0.19 −2.12 −0.13 −0.39 −1.04 −0.15 −0.25 −0.15 −0.51 −0.31 −0.26 −0.31 −0.24 −0.29 −0.55 0.08 −0.10 −0.10 −0.02 −1.17 0.10 −0.46

RMSE [PSU] 0.28 1.21 1.16 0.27 0.31 0.68 0.26 0.20 0.59 0.40 0.31 0.30 1.14 0.15 0.14 0.21 0.15 0.17 0.21 0.50 0.36 0.42 0.27

R 0.65 0.37 0.21 0.64 0.67 0.53 0.65 0.77 0.52 0.58 0.56 0.64 0.16 0.80 0.84 0.77 0.75 0.66 0.57 0.53 0.79 0.28 0.13

Number of records 1003 1052 996 541 557 557 846 828 918 798 945 956 823 339 310 333 349 187 182 574 565 207 192

Observation period 1958–2007 1958–2007 1962–2007

1958–2007 1958–2007 1958–2007 1959–2007 1986–2007

Germany and Poland, as well as in the Sea of Åland and in the shallow area between the Bothnian Sea and the Bothnian Bay. The intensified flows were also observed along the southern shores of the Gulf of Finland, as well as between the Gulf of Bothnia and the Baltic Proper. All these areas were characterised by surface flow rates in the range of 0.2–0.3 m s−1 and the rates over most of the Baltic Sea surface were 0.08–0.18 m s−1. The Baltic gulfs showed reduced values of the flow moduli relative to open waters. A comparison of mean annual moduli of the surface and subsurface currents revealed a velocity difference: the velocity of subsurface (20 m depth) currents was lower by about 0.1 m s−1. The actual velocities ranged from 0.02 to 0.1 m s−1, locally increasing to 0.14 m s−1 along the southern and eastern coasts and in

7

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Fig. 4. Vector fields of averaged currents in the Baltic Sea over the period 1958–2007 at the surface (a), at a depth of 20 m (b) and 40 m (c), and at the bottom (d).

Finland, and Bothnia (Fig. 7a). The weakest currents were observed in spring; their velocities increased in summer and then again in autumn to slightly decrease in winter (Fig. 7a–d). Stronger currents were observed in shallow areas such as the Słupsk Bank, the Middle Bank, Hoburg, Pomeranian Bay, off the Åland archipelago and in areas of specific shoreline contours with peninsulas and islands, inter alia, the Hel Peninsula, the Island of Rügen, Gotland, and Saaremaa. The seasonal vector fields showed circulation patterns consistent with their driving forces. Analysis of the spatial variability in the surface currents was supplemented by the exploration of anomalies. The vector fields of current anomalies showed a vectorial difference in each node from the mean annual flow field and seasonal fields. Thus, the anomalies did not reflect the vector flow patterns, but a difference in circulation in a given season relative to the mean current field. Deviations of seasonal circulations from the annual mean showed indications of pair-wise (winter-summer and spring-autumn) similarities. The winter anomalies exhibited slight differences in vectors between the mean annual current field and the field reflecting the winter flows (Fig. 8a). In the winter anomaly field, vectorial differences in the

Kattegat and along the eastern Baltic Proper coast indicated more intensive flows to the north compared to the mean annual flow pattern (Fig. 8a). Anomaly moduli of those vectors from the Kattegat to the Gulfs of Riga, Finland and Bothnia were higher than in the mean annual circulation (Fig. 9a). In the gulfs, the differences in moduli were smaller (negative), indicating slower currents compared to the mean annual circulation (Fig. 8c). As in winter, the differences in flows east of 20°E were longitudinal but southwards. The dominant vectorial differences in flows west of 20°E showed an eastern component. The direction and intensity of the flow field changed seasonally due to fluctuations in forcing. In winter, owing to the higher contribution of southerly winds, stronger northward flows were observed, particularly in the eastern part of the Baltic Sea. In summer, the increasing contribution of northerly winds resulted in meridional flows in the eastern areas. Easterly winds, most frequent in spring, produced westward currents throughout the Baltic Sea, particularly in the southern and eastern part of the Baltic Proper (Fig. 8b). In autumn, on the other hand, effects of westerly winds, producing anomalies of eastward currents, can be observed (Fig. 8d). 8

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Fig. 5. Fields of magnitude of the current velocity in the Baltic Sea averaged over the period of 1958–2007 at the surface (a), at a depth of 20 m (b) and 40 m (c), and at the bottom (d).

Higher anomalies, up to 0.07 m s−1, were observed in spring and autumn. The spring anomalies featured differences between spring flows and the annual average. They performed like a distinct western component, strongly stabilised in the southern and eastern part of the Baltic Sea (Fig. 8b). They were most pronounced from the southern entrance to the Gulf of Finland and the Pomeranian Bay. The autumn anomalies mirrored the spring anomalies, although they were reversed in the direction and were characterised by a slightly lower stability (Fig. 8d). A clear difference in spring anomalies resulted from the lowest velocities of the spring circulation compared to the pattern of annual means. Of all the seasons, the autumn surface circulation pattern and the spring anomaly proved to be the most pronounced. Anomalies of the magnitude of the current velocity fields showed pair-wise similarities identical to those of the seasonal current velocity fields (winter-autumn and spring-summer). The winter and autumn anomalies ranged from −0.03 m s−1 to +0.04 m s−1 in winter and

from −0.01 m s−1 to +0.06 m s−1 in autumn (Fig. 9a, d). The negative magnitude of the current velocity in autumn occurred locally, with small patches in the eastern Bornholm, western Gotland, and Bothnian basins. The positive magnitude of the velocity anomalies (higher than 0.03 m s−1) was prevalent throughout the Baltic Sea, particularly along the eastern coast. In contrast to autumn, large positive anomalies (higher than 0.05 m s−1) occurred in winter in the eastern part of the Gulf of Bothnia. In warm seasons, the negative magnitude of the current velocity anomalies of up to −0.05 m s−1 was dominant, particularly in spring (Fig. 9b, c). Positive values occurred marginally in some gulfs off the coasts. The negative magnitude of the current velocity anomalies occurred in the Baltic Proper as well as in the Gulfs of Bothnia and Finland, characterised by the slowest currents. In summer, positive magnitude anomalies occurred in the areas characterised by negative magnitude anomalies in winter (cf. Fig. 9a, c). The widest range of the 9

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Fig. 6. Seasonal surface current vector fields in the Baltic Sea averaged over the period of 1958–2007 in winter (a), spring (b), summer (c) and autumn (d).

velocity magnitude anomalies, from −0.05 to +0.05 m s−1, was recorded in summer. The seasonal circulation at a depth of about 20 m showed clear cyclonic circulation patterns and current stability of 0.3–0.7 (Fig. 10). The winter circulation pattern in the Gulf of Bothnia showed two cyclonic eddies. The Gulf of Finland and the Gulf of Riga showed weak western currents. Clear rotary motions were observed in the Baltic Proper and in the southern Baltic. The northern part of the Gotland Basin was a source of the current flowing in the south-western and southern directions along the Swedish coast, which first joined the vortex of the Bornholm Basin and then the vortex of the Arkona Basin. In the Gotland Basin, a well-developed latitudinal cyclonic circulation occurred (Fig. 10b). The winter circulation was similar to the mean annual circulation but was more stable. The circulation in spring and summer was similar to that in winter except for a lower intensity, particularly north of Gotland. In autumn, the pattern did not change, the flows were more intensive than in winter and the circulation patterns in the Gulf of Bothnia were more pronounced (Fig. 10a–d).

3.3. Seasonal and multi-annual variability of currents in the Baltic Sea This study showed that the Baltic Sea currents vary seasonally. The averaging of the current velocities across all the nodes over the Baltic Sea produced mean seasonal current velocities in each year (Fig. 11). These seasonal means, both for the surface and subsurface depths, were averaged for the whole period and their standard deviations were calculated (Table 4). In autumn, the surface moduli ranged within 0.15–0.21 m s−1; the spring magnitude of the current velocity ranged from 0.13 to 0.15 m s−1 (Fig. 11). The winters in the 1980s experienced a dynamic change in the current velocity, ranging from 0.12 to 0.19 m s−1, which indicates a surge and slowly decreasing oscillations in the last decade. The seasonally averaged magnitude of the current velocity (Table 4) at each depth showed a decrease from the autumn maxima to the spring minima. The average values ranged from 0.18 m s−1 at the surface to 0.09 m s−1 at a depth of 20 m, 0.07 m s−1 at 40 m and 0.04 m s−1 at the bottom. Considerably lower velocities occurred in spring (from 0.14 m s−1 at the surface to 0.06 m s−1 at the 10

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Fig. 7. Seasonal magnitude of the surface current velocity fields in the Baltic Sea averaged over the period of 1958–2007 in winter (a), spring (b), summer (c) and autumn (d).

subsurface levels, and 0.03 m s−1 at the bottom). The differences resulted from the high atmospheric activity in autumn and very low activity in spring. The current velocities in winter were slightly higher (about 0.05 m s−1) than in summer, except for those at the surface and at the bottom (Table 4). The analysis of trends at the surface in individual seasons showed

significantly decreasing trends, i.e. by 0.35, 0.25, 0.21 mm s−1 year−1 in winter, autumn and summer, respectively (Fig. 11; Table 5). The current velocity trend in spring was the only negative one and declined at a rate ranging from −0.08 mm s−1 year−1 at the surface and − 0.03 mm s−1 year−1 at the intermediate depths to zero near the bottom; however, these trends were not statistically significant. It can

Table 4 Seasonal averages (AVG) and standard deviation (SD) of the Baltic Sea surface, subsurface and bottom currents in 1958–2007. Depth [m]

0 20 40 Bottom

Winter

Spring

Summer

Autumn

Annual

AVG

SD

AVG

SD

AVG

SD

AVG

SD

AVG

SD

0.156 0.078 0.07 0.037

0.018 0.007 0.006 0.004

0.139 0.064 0.056 0.03

0.006 0.003 0.003 0.002

0.158 0.073 0.064 0.03

0.006 0.004 0.004 0.001

0.176 0.087 0.077 0.041

0.010 0.006 0.006 0.002

0.157 0.075 0.067 0.034

0.006 0.003 0.003 0.001

11

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Fig. 8. Seasonal variability of anomalies in surface currents in the Baltic Sea averaged over the period of 1958–2007 in winter (a), spring (b), summer (c), and autumn (d).

therefore be concluded that the annual increase in the current velocity in the Baltic during the period 1958–2007 resulted primarily from the increasing velocities in winter and autumn. The most pronounced growth trends at the surface occurred in winter, while in the subsurface depths – in autumn (Table 5). Seasonal changes in the mean current velocities were very weakly intercorrelated. It was only the linear correlation coefficient (0.32) between the mean magnitude of the surface current velocity for winter and autumn that was statistically significant. The mean current moduli varied from year to year. The highest annual mean (0.171 m s−1) was recorded in 1995, the lowest one (0.14 m s−1) was observed in 1987. The overall mean was 0.157 m s−1 (Fig. 12a; Table 4). The currents at 20 and 40 m were slower than those at the surface by 0.09 and 0.097 m s−1, respectively (Fig. 12b). The annual mean, minimum and maximum current moduli at 20 m were 0.075, 0.07 and 0.081 m s−1, respectively. At 40 m, the velocities were further reduced by 0.01 m s−1. The current velocity near the bottom was about two times lower (Fig. 12c).

Although the current trends were seasonally heterogeneous, the annual mean moduli of surface and subsurface currents showed increasing trends during the five decades (1958–2007) of the examined records (Fig. 12). The trend intensity changed gradually from 0.18 mm s−1 year−1 at the surface to 0.08 and 0.07 mm s−1 year−1 at the intermediate depths of 20 m and 40 m, to 0.03 mm s−1 year−1 near the bottom (Fig. 12; Table 5). During the analysed five decades, the mean annual current velocity was related to the changes in the vertical profile and varied from 0.14–0.17 m s−1 at the surface to 0.07 m s−1 at the depths of 20 m and 40 m to 0.03–0.035 m s−1 at the bottom. This means that the subsurface velocities were reduced by > 50% and the bottom currents were five times slower than the surface ones (Table 4). Fluctuations in the magnitude of the current velocity showed consistent oscillations around the trend lines. Their amplitudes decreased with increasing depth, and the fluctuation period was about 2.5 years. All depth levels showed growing trends. The strongest trend, observed at the surface, was slightly higher than 0.9 cm s−1 over 50 years 12

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Fig. 9. Seasonal variability of anomalies in the magnitude of the surface current velocity in the Baltic Sea averaged over the period of 1958–2007 in winter (a), spring (b), summer (c), and autumn (d).

(0.18 mm s−1 year−1). The increase in velocity over 50 years was 2–3 times lower at the subsurface depths compared to the surface. The bottom current velocity trend was also increasing, but at a five-fold lower rate (Table 4). During the first two decades (the 1960s and 1970s), the current velocity fluctuations were regular and showed low-amplitude oscillations (0.15 m s−1 and 0.16 m s−1, respectively). In the three subsequent decades, the amplitude increased 2.5 times with quasi-cyclic and overlapping long-term changes (Fig. 12). The mean annual currents in 1987 and 1995 (Fig. 13), i.e. the years of the highest (0.17 m s−1) and lowest (0.14 m s−1) magnitude of the surface current velocity, respectively, differed in flow rates and distinctness of eddies (or the absence thereof) (Fig. 13a, b). In 1995, the currents dominated by the eastern component were characterised by the most intensive flows near the Åland archipelago and from Bornholm via the Słupsk Trough to Gotland. The surface currents in 1987 (the

lowest flow rates) were characterised by a southward flow along the Swedish coast to Oland and cyclonic eddies in the Arkona, Bornholm and eastern Gotland basins, and in the Bothnian Sea (Fig. 13a). The spatially averaged magnitude of the current velocity distributions in both years was similar and related to the distribution averaged over the entire period of 50 years (cf. Fig. 4a). The differences involved flow rates and stability, which were higher in the years with higher current velocities. The areas with the highest velocities (about 0.28 m s−1) were located in the vicinity of islands: near the Åland Archipelago and off Gotland, Saaremaa, Hiumaa and Bornholm (Fig. 13c, d). 3.4. Relations between the Baltic current velocities and NAO index changes The variability of annual current velocities was related to the NAO index fluctuations. The annual surface current velocities, averaged across all the nodes throughout the Baltic Sea, were correlated with the 13

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Fig. 10. Seasonal current vector fields at a depth of 20 m in the Baltic Sea averaged over the period of 1958–2007 in winter (a), spring (b), summer (c), and autumn (c).

Fig. 11. Seasonal variability of mean annual Baltic Sea surface current moduli and their trends in 1958–2007. 14

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Table 5 Seasonal trend of the Baltic Sea surface, subsurface and bottom currents moduli; the slope of linear regression (SLR) and its standard error (SE) [mm s−1 year−1] in 1958–2007. Depth [m]

0 20 40 Bottom

Winter

Spring

Summer

Autumn

Annual

SLR

SE

SLR

SE

SLR

SE

SLR

SE

SLR

SE

0.35 0.11 0.08 0.07

0.17 0.071 0.063 0.033

−0.08 −0.03 −0.03 0.00

0.060 0.031 0.030 0.015

0.21 0.11 0.09 0.02

0.051 0.034 0.033 0.012

0.25 0.14 0.13 0.05

0.10 0.054 0.053 0.023

0.18 0.08 0.07 0.03

0.055 0.024 0.023 0.012

Bold values are statistically significant at the level of 0.05.

Fig. 12. Mean annual Baltic Sea current moduli in 1958–2007 for surface (a) and subsurface currents at a depth of 20 and 40 m (b), and at the bottom (c).

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Fig. 13. Mean annual vector fields of the Baltic Sea surface currents in 1987 (a) and 1995 (b) and their mean annual current moduli in 1987 (c) and 1995 (d).

winter NAO_djfm index (index values averaged over December–March) in the same period2 and the annual current velocity time course was compared with changes in the mean annual NAO index (Fig. 14); the correlation proved significant (R = 0.37). According to Hurrell (1995), the strongest atmosphere-sea interactions occur in winter. The correlation coefficient between NAO_djfm (December to March over 5 decades) and changes in the mean velocities of surface currents in the Baltic Sea was R = 0.66. As the NAO index represents a response of the sea to atmospheric forcing on the ocean spatial scale, regional indices were defined, e.g. the Baltic Sea Index (BSI; Lehmann et al., 2002). The calculated BSI_djfm was found to be strongly correlated (R = 0.8) with averaged surface current velocities in winter, V_winter (Fig. 15). An increase in the correlation coefficient indicates a closer interaction between currents and atmospheric activity on a regional scale. The BSI was strongly correlated (R = 0.88) with the NAO index, which results 2

from atmospheric forcing on a regional scale, embedded in that on the ocean-wide scale. Positive deviations from the trend line often matched the positive NAO index. When tested with Student's t-test, the correlation coefficient proved significant. Similar fluctuations in the currents and sea level in a period of just over four decades (1958–2001) compared to NAO_djfm showed correlations of R = 0.63 and R = 0.7, respectively (Jędrasik, 2014). The increase in mean wind velocities in the 1960s and 1970s resulted from the increasing (1–2% per year in 1958–2001) frequency of storms over the North Sea and the Baltic (Weisse et al., 2005). The increase in storminess in the 1970s was most pronounced in Northwestern Europe and less so in Central Europe (Matulla et al., 2008). In the 1980s, the most extreme storm events were connected with the positive NAO index associated with the increased number of extreme cyclones (Pinto et al., 2009). Some re-analyses suggested longterm upward trends in European storminess for the past 50 years, mostly over Northern Europe (Donat et al., 2011). Storminess and sealevel fluctuations at the Estonian coast in 1950–2011 were positively

NAO_djfm index values were adopted from Hurrell (1995). 16

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Fig. 14. The annual NAO_year index and NAO_djfm versus fluctuations of the average annual surface current velocity (V_year) in the Baltic Sea in 1958–2007.

Fig. 15. The NAO_djfm and BSI_djfm index versus fluctuations of the average winter surface current velocity (V_winter) in the Baltic Sea in1958–2007.

correlated with the NAO index (Jaagus and Suursaar, 2013). The last decade of the previous century was dominated by the positive NAO phase. At that time, the Baltic Sea was strongly influenced by atmospheric effects via the increased number of storms. The surface current system showed a wind speed-controlled increasing trend (0.02 cm s−1 per 10 years) of current velocity (Jędrasik, 2014). This corresponds with the increasing trend of the significant wave height in the Baltic Sea (Cieślikiewicz et al., 2004), the intensity of atmospheric system passages over the Baltic, and their correlation with the positive NAO index phase (Sepp, 2009). Two different annual surface circulations were compared. The first occurred in 1969 during the minimum of the negative phase NAO−, and the other one in 1989 with the positive phase NAO+. During the negative phase, the currents were dominated by those with the velocity ranging from 0.1 to 0.2 m s−1, with an annual average of 0.15 m s−1. During the negative phase, the flows increased to 0.17 m s−1 and the velocity range increased to 0.2–0.5 m s−1. The relatively slow surface circulation in 1969 involved current velocities below 0.2 m s−1 in the Kattegat, at the Bornholm Gate, along the Sambia Peninsula and in the northern part of the Bothnian Sea (Fig. 16a). Weak cyclonic circulation patterns were preserved in the Bornholm Deep and the East Gotland Deep as well as in the Bothnian Sea and the Bothnian Bay. When the NAO index reached its maximum in the analysed five decades (1989, positive phase), the areas with significantly increased flows at a velocity of 0.2–0.5 m s−1 included the Kattegat, Bornholm and Gdańsk Basins as well as the Åland and Bothnian Seas. The surface currents were characterised by a flow direction from west to east. The weak

currents flowing westwards in 1969 and the strong flow towards the east in 1989 confirmed the effects of atmospheric forcing on the nature of the Baltic Sea circulation as being related to the NAO phase (Fig. 16). 4. Discussion Due to the lack of sufficiently long current observation series, the PM3D model validation was indirect on the assumption that the agreement between the modelled and observed sea levels proves a good approximation of barotropic currents by the model. On the other hand, a good fit between the modelled and observed temperature and salinity at the monitoring stations distributed throughout the Baltic Sea proves the reliability of baroclinic flow modelling. The validation showed a good agreement both in the surface and subsurface layers, mostly due to the fact that the 50-year simulation did not involve data assimilation. The fit was worse in the case of deep, below-halocline layers, which requires caution regarding the modelling results for these layers. The study focused on long-term (5 decades) flows driven by climate (atmospheric conditions) and bottom topography, hence the 3 NM resolution proved optimal. A PM3D with a higher resolution (0.5 NM, 1 NM) has already been used for the Baltic Sea, but for shorter simulation periods (Kowalewski and Kowalewska-Kalkowska, 2017). The model resolution adopted in this work resulted from a long time necessary to produce a 50-year simulation (3 NM resolution required 43 days of computing time, and more that 250 days would be needed for 1 NM resolution). To describe eddy-like structures that arise from saline water inflows from the North Sea, a resolution finer than 1 NM is necessary. 17

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Fig. 16. Mean annual surface current vector fields in the Baltic Sea in 1969 (a) and 1989 (b).

water from the North Sea, entering via the Danish Straits, naturally and “easily” penetrates the Arkona Deep and continues via the deep Bornholm Gate to the Bornholm Deep. These quasi-permanent bottom inflows into the Bornholm Deep do not continue so regularly in the Baltic Proper. Further migrations of the benthic water occur at a wind sequence from north to east, producing a surge in the western part of the Baltic and moving the benthic water eastwards (Krauss and Brϋgge, 1991). The eastward flows with a similar stability occur in the eastern part of the Słupsk Trough as well as in the Åland and Bothnian Seas. The surface and subsurface currents, prevailing in the Baltic, are driven by wind, because current velocities are the response to forcing. The upward trend in the velocity of currents is the result of increasing wind velocity in the period 1958–2007. A long-term increase in wind speed is related to the presence of baric lows or their increased frequency or else to an increased number of deep lows. Baric lows imply increased dynamics at the sea surface. On the other hand, baric highs (often stationary) are accompanied by weak and moderate winds. The analysis of the frequency of baric lows over the Baltic Sea in 1948–2002 showed a positive correlation between the NAO index and the number of deep lows (air pressure at the sea surface < 1000 hPa) (Sepp, 2009). On average, 43 lows occurred annually over the Baltic Sea. The deep cyclonic systems have increased by 11% from the beginning (36%) to the end (47%) of the analysed period (Sepp, 2009). The study of climate change in the Baltic Sea region in the period of 1958–2009 (Lehmann et al., 2011) showed that since the 1970s the number of deep cyclones (< 980 hPa) has been continuously increasing and follows their centres in the North Atlantic from Iceland towards the Arctic in NE. At that time, winter geostrophic winds increased from 0.5 m s−1 in the northern part to 1.5 m s−1 in the southern and middle part of the Baltic Sea. Geostrophic winds in spring increased by 0.5–1.0 m s−1 in all subregions of the Baltic. In contrast, the geostrophic winds in autumn decreased by 1.5–2 m s−1 in the western and central parts of the Baltic Sea. The analysis of data from ERA-40 for the period 1958–2001 showed a growing trend in winter wind speeds and a shift in deep cyclones further NE towards the Arctic, increasing the impact on the Baltic Sea (Lehmann et al., 2011). The multi-decadal (1958–2001) study of the Baltic Sea wave field showed long-term changes in the wind-driven wave activity coincident with changes in wind conditions over the Baltic Sea and in the NAO index. The significant wave height showed an increasing trend from 2.5 to over 5 mm year−1 in the western and eastern part of the Baltic Sea,

The episodic oceanic inflows into the Baltic Sea generate baroclinic water structuring, with flows in the form of mesoscale eddies. They were estimated based on the long-term series of measurements in the Baltic and scaled using the Rossby internal radii, ranging from 7.3 km in the Bornholm Basin to 1.3 km in the Gulf of Finland (Fennel et al., 1991; Osiński et al., 2010). To describe mesoscale structures, the eddy-permitting models require at least 2 horizontal nodes; 4–5 nodes are necessary in the eddy-resolving models (Sein et al., 2017). Thus, the horizontal resolution applied (3 NM or 5.5 km) did not allow modelling of baroclinic eddies. This makes it possible to model a basin-sized eddy structure as well as cyclonic and anticyclone circulation patterns. The modelling accounted for, albeit in a simplified manner, the presence of the sea ice by setting heat and moment fluxes on the surface to zero when the water temperature was at the freezing point. This solution works relatively well when fast ice occurs for longer periods of time. Then, the atmospheric forcing in the weather model keeps the surface water temperature close to the freezing point, which reduces the energy exchange through the surface. On the other hand, the simplification may lead to certain errors when the sea surface is only partially covered by ice, e.g. during the initial phase of ice formation and at the beginning of ice thawing. However, the results of the model validation with respect to the sea level (Table 1) showed no significant errors for stations situated in the ice-prone areas compared to the remaining parts of the Baltic Sea. This means that the applied solution correctly approximated the wind stresses on the surface of the sea and the ice. With respect to the surface temperature, the statistical errors (RMSEs) were slightly larger at the ice-prone stations (A13, LL7 and 16) compared to other locations (Table 2), which may be related to the simplified solution for the ice. However, the errors of 1.2–1.4 °C are fairly small, considering no data assimilation. In the case of salinity, even lower RMSEs (0.15 PSU) were obtained for the Bothnian Bay (A13 and SR5) compared to the open Baltic waters, although they were larger in both the Gulf of Finland (LL7) and the Gulf of Riga (16). It seems, however, that the salinity modelling precision may have been more affected by the quality of riverine inflow data rather than the ice cover. The results of the model validation suggest that the simplification for the sea ice did not have a particularly strong impact on modelling effects, although effects of the sea ice on the Baltic circulation should be further studied. The near-bottom currents in the Kattegat, Oresund, Arkona Deep, and Bornholm Gate are very stable (0.6–0.7; Fig. 4d). The highly saline 18

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respectively (Cieślikiewicz et al., 2004). The significant increase in the wave height, resulting from the increased wind speed, corresponds to the increased current velocity. The results obtained in this study on the variability of current moduli showed velocities of 0.2–0.3 m s−1 in shallow areas and slower (0.08–0.18 m s−1) currents in deeper areas. Such spatial distributions of the currents are supported by models of flow rates and sediment transport, and are reflected in sediment deposition (Krauss and Brϋgge, 1991; Kuhrts et al., 2004). In the analysed hindcast model, simulations of two extreme annual mean flow rates were selected (in 1987 and 1995). They correspond with the positive and negative NAO phases, respectively. The positive phase was associated with the strong western circulation and Baltic infilling, whereas the negative phase was connected with the intensified outflow to the North Sea. The result obtained is supported by studies of Lehmann et al. (2002). Since 1980, the NAO index has been more frequently positive. In 1983, 1989 and 1992, it reached the highest values since 1864 (i.e. in > 140 years). In addition to the analysis of the NAO index, Lehmann et al. (2002) developed a regional index, i.e. the Baltic Sea Index (BSI) that takes into account atmospheric pressure differences between Szczecin and Oslo. They demonstrated that the positive BSI phase is associated with strong Ekman currents with up- and downwellings along the coasts. The negative BSI phase was accompanied by weak winds, with reduced drift currents and upwellings; the flow field was described by the barotropic current function (Lehmann et al., 2002).

atmospheric effects. The relationship demonstrated for 1958–2007 was indicative of potentially similar effects during periods not covered by this study. Variations in the NAO index reflect changes in atmospheric conditions, which determine the nature of 3D water circulation, sealevel changes and the amount of inflows into the Baltic Sea. The NAO index in the 1960s was dominated by negative values, while the positive phase prevailed in the 1990s. During the dominance of the positive NAO phase, the Baltic Sea was strongly affected by the atmosphere through the increased number of storms. The recent decade with the predominantly negative NAO phase featured severe winters with extensive ice cover and low water temperature. The negative NAO phase is associated with milder hydrodynamics, fewer inflows and thus longer stagnation of the water column, which may result in the deterioration of environmental conditions in the Baltic Sea ecosystem. Less intense hydrodynamics will hinder the morphodynamic processes affecting the shore; however, due to the increase in the amount and intensity of ice phenomena, the effects of ice in sheltered areas of embayments and lagoons will be intensified. The results of seasonal and long-term modelling of the Baltic Sea currents allowed to identify climatic trends in current velocities in the analysed period of 50 years and to develop maps of currents and their stability at different depths. The identified circulation patterns may be used in studies of the wind-driven and thermohaline circulation in the Baltic Sea (Lehmann and Hindrichsen, 2000a, 2000b). Such information may also be used for ecosystem studies in respect of water exchange, organic and inorganic matter transport, pollutant dispersal, eutrophication and other problems. Knowledge of currents and their stability was applied to study the dynamics of secondary spread of invasive species in western Eurasia (Jaspers et al., 2018).

5. Conclusions The currents modelled over five decades provided new knowledge on the Baltic Sea currents and confirmed the pattern of eddy circulation, known from previous studies covering periods shorter than two decades (Lehmann, 1995; Lehmann and Hindrichsen, 2000a.b; Meier, 1999; Meier and Kauker, 2003). The first novel characteristic of the circulation, revealed in this study, involved higher stability of subsurface currents (0.4–0.7) relative to the ephemeral surface currents (0.2–0.5) and the distinct cyclonic circulation in the Baltic deeps (Arkona, Bornholm and Gotland) as well as in the Bothnian Sea and the Bothnian Bay. The intensified flows occurred in shallow areas off the islands and along the eastern Baltic coast. The subsurface (20, 40, 60 m and near-bottom) circulation was less dependent on atmospheric effects and more dependent on bottom topography. The second characteristic of the Baltic Sea current system was the opposite patterns of circulation anomalies in spring and autumn and the similarity between the winter and summer circulation. The spring circulation was characterised by outflows from the Baltic Sea at a lowered level of the free surface. This was confirmed by higher outflows in the water exchange with the North Sea. The autumn circulation, dominated by eastward currents, generated inflows and large infilling of the Baltic Sea. The third characteristic of the surface currents was a wind speedcontrolled growing trend of their velocities (0.18, 0.08, 0.07 and 0.03 mm s−1 year−1 at the surface, at a depth of 20 and 40 m, and at the bottom per 50 years, respectively) associated with the dominance of the positive NAO index phase. Fluctuations of current velocity around the trend line correlated positively (R = 0.66) with the NAO_djfm. This result corresponds with increasing trends of the significant wave height in the Baltic Sea (Cieślikiewicz et al., 2004), the intensity of baric system migrations over the Baltic (Sepp, 2009) and their positive correlation with the positive NAO index phase. The significant and high correlation between the NAO index and the modelled hydrodynamic parameters (long-term changes of the sea level and surface current velocities) showed that they are dependent on

Acknowledgements This research was financed by the Institute of Oceanography of the University of Gdańsk. Bathymetric data used for the construction of the 3 NM grid for the Baltic Sea were provided by the Institute of Oceanography, University of Gdańsk (IOUG), the Institut für Ostseeforschung in Warnemünde (IOW),3 the Gdynia Naval Hydrographic Office, and the Maritime Institute in Gdańsk (MIG). Atmospheric forcing for the period 1958–2001 was performed (as in the EU Project HIPOCAS)4 using the REMO regional atmospheric climate model (REgionalMOdel) (Jacob and Podzun, 1997) based on the EM numerical weather prediction model of the German Weather Forecast Service (DWD). We are grateful to Frauke Feser for sharing REMO model data for the period 2002–2007 (Feser et al., 2001). We wish to thank Peeter Ennet from the Estonian Environment Agency, Räike Antti from the Finnish Environment Institute (SYKE), Svajunas Plunge from the Hydrographic Network Division Environmental Protection Agency in Lithuania, and Lars Sonesten from the Swedish University of Agricultural Sciences (SLU) for granting us access to data sources on the mean monthly values of river discharges into the Baltic in their respective areas for the period 1990–2007. We are very thankful to Miguel Rodriguez Medina from the Nest Institute in Sweden for sharing with us the data on riverine outflow into the Baltic Sea from the Baltic Environment Database for the period 1970–2007. We express our thanks to the Institute of Meteorology and Water Management (IMWM) in Warsaw for sharing records of the sea-level fluctuations at the Polish coast from the stations in Świnoujście, Kołobrzeg, Ustka, Władysławowo, and Gdańsk Nowy Port for the period 1958–2007 as well as daily flow measurement data in the Vistula and Oder river mouth profiles over the period 1958–2007.

3

See Seifert and Keiser (1995). The HIPOCAS EU Project (Hindcast of Dynamic Processes of the Ocean and Coastal Areas of Europe) – Project No. EVK2-CT-1999-00038. 4

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Annex

Fig. A1. Comparison of the observed (dots) and modelled (line) water temperature at station A13 over the period of 1958–2007 at sea surface (a), at a depth of 50 m (b) and 90 m (c).

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Fig. A2. Comparison of the observed (dots) and modelled (line) water temperature at station BY15 over the period of 1958–2007 at sea surface (a), at a depth of 50 m (b) and 150 m (c).

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Fig. A3. Comparison of the observed (dots) and modelled (line) water temperature at station BY5 over the period of 1958–2007 at sea surface (a), at a depth of 50 m (b) and 70 m (c).

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Fig. A4. Comparison of the observed (dots) and modelled (line) salinity at station A13 over the period of 1958–2007 at sea surface (a), at a depth of 50 m and 90 m (c).

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Fig. A5. Comparison of the observed (dots) and modelled (line) salinity at station BY15 over the period of 1958–2007 at sea surface (a), at a depth of 50 m and 150 m (c).

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Fig. A6. Comparison of the observed (dots) and modelled (line) salinity at station BY5 over the period of 1958–2007 at sea surface (a), at a depth of 50 m (b) and 70 m (c).

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