For two future scenarios on the expansion of offshore wind power in the Baltic Sea and the North Sea, SMHI has investigated how the hydrography, i.e. temperatures, salinities, currents and stratification, may be affected. Effects were induced by wind stress reductions on the sea surface and by the increased friction and turbulence in the water from wind turbine foundations.

The results show that an expansion of wind power in the Baltic Sea in general will cause a shallowed halocline, and increased deep water salinities and temperatures, due to decreasing winds behind the wind farms that lead to decreasing vertical mixing in the Baltic Sea. However, the magnitude of changes shows a strong sensitivity to assumptions about the wind stress reduction at the sea surface, and the size of wind power expansion.

The wind farm scenarios are prepared in collaboration with the Swedish Agency for Marine and Water Management (SwAM) and are based on marine plans from Sweden’s neighbouring countries as well as new proposals for suitable wind power areas that SwAM will present to the government in 2024. In one scenario, Scenario 1, it is assumed that there will be offshore wind in all proposed areas, while in the second scenario, Scenario 2, it is assumed that only 50% of areas will be developed. Both scenarios represent large offshore wind power developments that will probably not be realized in reality. The scenarios have been investigated by running an ocean model for the Baltic Sea and the North Sea with and without wind power for the period 1985 – 2016 to evaluate how different the sea would have looked if the wind power had been built in 1985 according to the scenarios.

There is still lack of knowledge about how wind farms affect the wind at the sea surface, so this work is based on studies of existing wind farms in the North Sea, where studies show a reduction of the wind by around 8% and an area that extends about 30 km behind the wind farm under stable atmospheric conditions. When the atmosphere is unstable, which it often is in winter, the reduction is less. In order to get an estimate of the largest and smallest possible impact of wind power on the sea, we have therefore, for both scenarios, assumed that the reduction of wind only exists in summer and no reduction during winter (minimum possible impact), or that the reduction exists all year round (upper limit of impact).

The magnitude of expected changes is very dependent on the assumptions on the wind wakes, and the response is much smaller for the minimum possible impact than for the upper limit impact. The real response for these scenarios probably lays somewhere in between these estimates.

For the scenario with less wind farms in Swedish waters (Scenario 2), the influences on salinity, temperature, and halocline are reduced relative to Scenario 1 in a manner that may be expected from the difference in total wind farm areas in the Baltic Sea in the two scenarios.

The model results also show that the wind power foundations (modelled as bottom mounted) cause a salinity decrease in the Baltic Sea deep water, probably due to increased friction and mixing in the entrance region to the Baltic Sea. This effect is much smaller than the wind wake effect when it is active during the whole year.

The Baltic Sea surface salinity, surface temperature, and currents show much smaller and less robust changes than the salinity and temperature changes in the deepwater.

Oceanographic observations are often of high quality but are available only with low resolution in time and space. On the other hand, model fields have high resolution in time and space but are not necessarily in agreement with observations. To bridge the gap between these very different kinds of data sets, a reanalysis can be made, which means that fixed versions of the numerical model and the data assimilation system are used to analyse a period of several years. This report describes an oceanographic reanalysis covering the period 1990 to 2004 (15 whole years). The horizontal resolution is 3 nautical miles in the Baltic Sea and 12 nautical miles in the North Sea, and the vertical resolution varies between 4 meters near the surface to 60 meters in the deepest part (up to 24 vertical layers). The time resolution of the reanalysis product is 6 hours. The numerical ocean model used is HIROMB (High-Resolution Operational Model for the Baltic), version 3.0. The data assimilation method used in this reanalysis is the Successive Corrections Method (SCM) for salinity and temperature, whereas ice observations in terms of ice charts were simply interpolated. The result looks good in terms of sea levels, ice fields, and salinity and temperature structure, whereas currents have not been validated. This oceanographic reanalysis was probably the first one ever for the Baltic Sea (when it was done in 2005) and may serve as a starting point before longer, more advanced reanalyses are produced.

Historical oceanographic data from the period 1964-1997 from two deep subbasins (the Gotland Deep and the Landsort Deep) in the Baltic Sea have been analyzed, by using a budget method on stagnant periods, with respect to vertical diffusion and vertical energy flux density in the deep water. It was found that the rate of deepwater mixing varied with the seasons, with higher rates in fall and winter compared to spring and summer. Further, according to the analyzed data, the downward flux density of energy available for vertical diffusion decreased with increasing depth in the Gotland Deep. In the Landsort Deep, however, the flux density increased somewhat, probably because of topographic concentration of the energy, before decreasing toward the bottom. Moreover, the vertical energy flux densities were compared with the expected flux density from the local wind. It is proposed that in the Gotland Deep, which is outside the coastal boundary layer, the observed deepwater mixing is dominated by the energy input from the wind via inertial currents and internal waves. In the Landsort Deep, however, which is within the coastal boundary layer, the expected flux density of energy from the local wind cannot explain the observed rate of work against the buoyancy forces. It is proposed that the active coastal boundary layer plays a central role in the transfer of energy to mixing processes in the deep water.

[1] A one-dimensional numerical ocean model of the southern Baltic Sea is used to investigate suitable parameterizations of unresolved turbulence and compare with available observations. The turbulence model is a k-epsilon model that includes extra source terms P-IW and P-LC of turbulent kinetic energy (TKE) due to unresolved, breaking internal waves and Langmuir circulations, respectively. As tides are negligible in the Baltic Sea, topographic generation of internal wave energy (IWE) is neglected. Instead, the energy for deepwater mixing in the Baltic Sea is provided by the wind. At each level the source term P-IW is assumed to be related to a vertically integrated pool of IWE, E-0, and the buoyancy frequency N at the same level, according to P-IW (z) proportional to E0Ndelta (z). This results in vertical profiles of epsilon (the dissipation rate of TKE) and K-h (the eddy diffusivity) according to epsilon proportional to N-delta and K-h proportional to Ndelta-2 below the main pycnocline. Earlier observations are inconclusive as to the proper value of delta, and here a range of values of delta is tested in hundreds of 10-year simulations of the southern Baltic Sea. It is concluded that delta = 1.0 +/- 0.3 and that a mean energy flux density to the internal wave field of about (0.9 +/- 0.3) x 10(-3) W m(-2) is needed to explain the observed salinity field. In addition, a simple wind-dependent formulation of the energy flux to the internal wave field is tested, which has some success in describing the short- and long-term variability of the deepwater turbulence. The model suggests that similar to16% of the energy supplied to the surface layer by the wind is used for deepwater mixing. Finally, it is also shown that Langmuir circulations are important to include when modeling the oceanic boundary layer. A simple parameterization of Langmuir circulations is tuned against large-eddy simulation data and verified for the Baltic Sea.

A 3-D ensemble variational (3DEnVar) data assimilation method has been implemented and tested for oceanographic data assimilation of sea surface temperature (SST), sea surface salinity (SSS), sea ice concentration (SIC), and salinity and temperature profiles. To damp spurious long-range correlations in the ensemble statistics, horizontal and vertical localisation was implemented using empirical orthogonal functions. The results show that the 3DEnVar method is indeed possible to use in oceanographic data assimilation. So far, only a seasonally dependent ensemble has been used, based on historical model simulations. Near-surface experiments showed that the ensemble statistics gave inhomogeneous and anisotropic horizontal structure functions, and assimilation of real SST and SIC fields gave smooth, realistic increment fields. The implementation was multivariate, and results showed that the cross-correlations between variables work in an intuitive way, for example, decreasing SST where SIC was increased and vice versa. The profile data assimilation also gave good results. The results from a 25-year reanalysis showed that the vertical salinity and temperature structure were significantly improved, compared to both dependent and independent data.

A one-equation turbulence model is presented, in which the turbulent kinetic energy k is calculated with a transport equation whereas the turbulent length scale l is calculated with an algebraic expression. The value of l depends on the local stratification and reduces to the classical kappa vertical bar z vertical bar scaling for unstratified flows near a wall, where vertical bar z vertical bar is the distance to the wall. The length scale decreases during stable stratification, and increases for unstable stratification compared to the neutral case. In the limit of strong stable stratification, the so-called buoyancy length scale proportional to k(1/2)N(-1) is obtained, where N is the buoyancy frequency. The length scale formulation introduces a single model parameter which is calibrated against experimental data. The model is verified extensively against laboratory measurements and oceanic data, and comparisons are made with the two-equation k-epsilon model. It is shown that the performance of the proposed k model is almost identical to that of the k-epsilon model. In addition, the stability functions of Launder are revisited and adjusted to obtain better agreement with recent data.

This paper presents a method for joint retrieval of the ocean surface wind and current vectors using the backscatter and the Doppler frequency shift measured by spaceborne single-beam single-polarization synthetic aperture radar (SAR). The retrieval method is based on the Bayesian approach with the a priori information provided by atmospheric and oceanic models for surface wind and currents, respectively. The backscatter and Doppler frequency shift are estimated from the along-track interferometric SAR system TanDEM-X data. The retrieval results are compared against in-situ measurements along the Swedish west coast. It is found that the wind retrieval reduces the atmospheric model bias compared to in-situ measurements by about 1 m/s for wind speed, while the bias reduction in the wind direction is minor as the wind direction provided by the model was accurate in the studied cases. The ocean model bias compared to in-situ measurements is reduced by about 0.04 m/s and 12 circle for current speed and direction, respectively. It is shown that blending SAR data with model data is particularly useful in complex situations such as atmospheric and oceanic fronts. This is demonstrated through two case studies in the Skagerrak Sea along the Swedish west coast. It is shown that the retrieval successfully introduces small scale circulation features detected by SAR that are unresolved by the models and preserves the large scale circulation imposed by the models.

Multi-model ensembles for sea surface temperature (SST), sea surface salinity (SSS), sea surface currents (SSC), and water transports have been developed for the North Sea and the Baltic Sea using outputs from several operational ocean forecasting models provided by different institutes. The individual models differ in model code, resolution, boundary conditions, atmospheric forcing, and data assimilation. The ensembles are produced on a daily basis. Daily statistics are calculated for each parameter giving information about the spread of the forecasts with standard deviation, ensemble mean and median, and coefficient of variation. High forecast uncertainty, i.e., for SSS and SSC, was found in the Skagerrak, Kattegat (Transition Area between North Sea and Baltic Sea), and the Norwegian Channel. Based on the data collected, longer-term statistical analyses have been done, such as a comparison with satellite data for SST and evaluation of the deviation between forecasts in temporal and spatial scale. Regions of high forecast uncertainty for SSS and SSC have been detected in the Transition Area and the Norwegian Channel where a large spread between the models might evolve due to differences in simulating the frontal structures and their movements. A distinct seasonal pattern could be distinguished for SST with high uncertainty between the forecasts during summer. Forecasts with relatively high deviation from the multi-model ensemble (MME) products or the other individual forecasts were detected for each region and each parameter. The comparison with satellite data showed that the error of the MME products is lowest compared to those of the ensemble members.

The Baltic Sea is a marginal sea, located in a highly industrialized region in Central Northern Europe. Saltwater inflows from the North Sea and associated ventilation of the deep exert crucial control on the entire Baltic Sea ecosystem. This study explores the impact of anticipated sea level changes on the dynamics of those inflows. We use a numerical oceanic general circulation model covering both the Baltic and the North Sea. The model successfully retraces the essential ventilation dynamics throughout the period 1961-2007. A suite of idealized experiments suggests that rising sea level is associated with intensified ventilation as saltwater inflows become stronger, longer, and more frequent. Expressed quantitatively as a salinity increase in the deep central Baltic Sea, we find that a sea level rise of 1 m triggers a saltening of more than 1 PSU. This substantial increase in ventilation is the consequence of the increasing cross section in the Danish Straits amplified by a reduction of vertical mixing.

Information about ice is indispensable to navigation in ice-covered sea areas. For vessels traveling long distances in ice, it is worth planning routes that will reduce fuel consumption and travel time, as well as the risk of ending up in hazardous areas or getting stuck in the ice. In addition to observations on board. there is a multitude of data sources available for seafarers like satellite images, ice model data, weather observations and forecasts. However, it is difficult for a human to take into consideration all the time-varying data parameters when planning a route. In this paper, a prototype system for optimizing routes through the ice field is presented. The system integrates state-of-the-art ice modeling, ship transit modeling, and an enduser system as a route optimization tool for vessels navigating in ice-covered waters. The system has recently been validated on board merchant vessels in the Baltic Sea, and the system's performance has been analyzed statistically using AIS data. Based on the AIS data analysis the mean relative error of the estimated transit time was 0.144 [s/s] with a standard deviation of 0.147 [s/s] for long routes (90-650 km), and 0.018 [s/s] with standard deviation of 0.193 [s/s] for 50 km route segments. (C) 2008 Elsevier B.V. All rights reserved.

Newly developed ecosystem model NEMO-Nordic-SCOBI was applied to Skagerrak - Kattegat area to investigate the variability of some indicators of the ecosystem. Also, two sensitivity runs were performed to investigate possible effect of the Baltic Sea Action Plan (BSAP) and a river loads reduction scenario on the Skagerrak - Kattegat area. The performed investigation could be used “to provide a basis to assist with the interpretation of measurement data before the Intermediate Assessments Eutrophication status assessment”. Comparison of simulation results with observations indicates acceptable model performance. Modeled sea surface salinity, temperature and dissolved inorganic phosphate (DIP) are in good agreement with observations. At the same time, the model has a bias in certain areas of the investigated region for dissolved inorganic nitrogen (DIN) and dissolved silicate during the winter season. However, the model in its current state shows good enough results for the performed investigation. Results of the two sensitivity studies show a decrease of sea surface nutrients concentrations during winter period in both regions. In the Skagerrak area the decrease is due to reduction in river nutrient loads in North Sea. In the Kattegat area there is a decrease of dissolved phosphate due to the implementation of BSAP. At the same time, in both scenarios, no significant changes were obtained for near bottom oxygen or surface layer Chl-a.

A 30-year (1970-1999) reanalysis of temperature and salinity is conducted by assimilating temperature and salinity profiles into an ocean model of the Baltic Sea with ensemble optimal interpolation approach. Some configurations of the reanalysis are presented. For example, the samples are chosen from the same season as the analysis time to address the strong seasonal variability. The impact of different observation time windows on the analysis results is also discussed. A locally determined alpha is adopted for the long-time-scale simulation. To assess the accuracy of the reanalysis, a set of comparisons between the reanalysis results and the free run results was performed. The root mean square deviations (RMSDs) between the reanalysis results and not-yet-assimilated observations at all levels show that, compared to the free run, temperature and salinity have been improved significantly, that is, by 31.1 and 38.8%, respectively. The vertical structure of the reanalyzed fields is also adjusted. The reanalysis results show that the improvements in both temperature and salinity are smaller at greater water depths. Comparison with independent CTD data, the reanalysis significantly improved temperatures and salinities in all layers relative to the free run. For temperature and salinity during the period of ship voyages, the RMSDs are reduced by 32.9 and 25.5%, respectively. The temporal variations of the deep-water salinity caused by saltwater inflows are better captured by the reanalysis than by the free run. Moreover, the reanalysis improved the estimation of the depth of the halocline and thermocline, which are overestimated in the simulation without data assimilation.

The Baltic Sea is a seasonally ice-covered marginal sea located in a densely populated area in northern Europe. Severe sea ice conditions have the potential to hinder the intense ship traffic considerably. Thus, sea ice fore-and nowcasts are regularly provided by the national weather services. Typically, the forecast comprises several ice properties that are distributed as prognostic variables, but their actual usefulness is difficult to measure, and the ship captains must determine their relative importance and relevance for optimal ship speed and safety ad hoc. The present study provides a more objective approach by comparing the ship speeds, obtained by the automatic identification system (AIS), with the respective forecasted ice conditions. We find that, despite an unavoidable random component, this information is useful to constrain and rate fore-and nowcasts. More precisely, 62-67% of ship speed variations can be explained by the forecasted ice properties when fitting a mixed-effect model. This statistical fit is based on a test region in the Bothnian Sea during the severe winter 2011 and employs 15 to 25 min averages of ship speed.

The Baltic Sea ice is strongly influenced by the atmospheric circulation and  shows large interannual variability. At the same time the Baltic Sea is one of the most investigated regions on earth with long ice time series. To detect trends in climate change and to relate these to natural or anthropogenic causes are of central importance in the present Baltic Sea research. This was also the main topic during the Fourth Workshop on Baltic Sea Ice Climate held in Norrköping, 22-24 May, 2002. The workshop was organised by SMHI, the SWECLIM program, the Department of Oceanography at the Earth Sciences Centre of Göteborg University, and the Swedish Maritime Administration.

Salinity and temperature variations in the Baltic proper and the Kattegat have been analyzed with a numerical ocean model and a large amount of observational data. In the model, the Baltic Sea is divided into 13 sub-basins with high vertical resolution, horizontally coupled by barotropic and baroclinic flows and vertically coupled to a sea-ice model which includes dynamics as well as thermodynamics. The model was integrated for a 15-year period (1980-1995) by using observed meteorological forcing data, river-runoff data and sea-level data from the Kattegat. The calculated 15-year median profiles of salinity and temperature in the different sub-basins are in good agreement with observations. However, the calculated mid-depth salinities in the Arkona Basin and Bornholm Basin were somewhat overestimated, and the calculated deep-water temperatures in the Arkona Basin and the Bornholm Basin are somewhat lower than the observed values. Frontal mixing and movements in the Kattegat and the entrance area of the Arkona Basin were important to consider in the model. Water masses were simulated well, and prescribing constant deep-water properties in the Kattegat proved to be a reasonable lateral boundary condition. Further, comparisons were made between observed and calculated seasonal and interannual variations of the hydrographic properties in the Eastern Gotland Basin, as well as the interannual variations of the annual maximum ice extent. We conclude that the model can simulate these variations realistically. The major Baltic inflow of 1993 was also simulated by the model, but the inflowing water was 1-2 degrees degrees too cold. Finally, the response times to changes in forcing of the Baltic proper and the Kattegat were investigated by performing the so-called lock-exchange experiment. Typical stratification spin-up times were of the order of 10 years for the Kattegat, and 100 years for the Baltic proper.

The modeling of salinity and temperature in Gulf of Bothnia, Gulf of Finland, and Gulf of Riga is investigated by using a coupled sea ice-ocean Baltic Sea model. 18 years, from late 1980 to the end of 1998, have been investigated. The forcing data extracted taken from a gridded meteorological data base, sea level data from the Kattegat, and river runoff data to the different subbasins of the Baltic Sea from a hydrological data base. To improve the gridded meteorological data base a statistical model for the reduction of geostrophic winds to surface winds was developed. In the analysis it was shown that the calculated long-term salinity and temperature structures were stable and in good agreement with observations. This was made possible by using three different strait-flow models connecting the subbasins of the Baltic Sea. The seasonal and interannual variations of temperature and salinity were also well simulated by the model, implying that the coupling between the atmosphere and the Baltic Sea as well as the diapycnal mixing are reasonably well understood. The water cycle and the surface heat balance were calculated using the 18-year simulation. In the water-balance calculations it was shown that the volume flows from the large gulfs of the Baltic Sea were mainly due to baroclinic transports and that net precipitation added freshwater during the Studied period, particularly to the large gulfs. From the heat-balance calculation it is concluded that the Baltic Sea is almost in local balance with the atmosphere. The Bothnian Bay, Gulf of Finland and Gulf of Riga loose heat, whereas the Bothnian Sea gains heat, calculated as long-term means. (C) 2003 Elsevier Science Ltd. All rights reserved.

SMHI has analysed how sea ice conditions in the Bothnian Bay, Bothnian Sea, Åland Sea and northern Baltic Proper may change in a 20 and 50 year perspective relative to 2020. The study is focused on seven indicators describing different aspects of sea ice change. The indicators were identified jointly with the Swedish Maritime Administration (SMA), and chosen based on available data and relevance to ice breaking.The study is based on historical observations from SMHI, the Finnish Meteorological Institute (FMI) and SMA, and climate scenario data from previous projects.Climate scenarios representing two different representative concentration pathways (RCP4.5 and RCP8.5) have been analysed based on a total of ten different climate model simulations. Scenarios based on the lower representative concentration pathway (RCP2.6) are absent because existing datasets for this pathway do not have sufficient quality for sea ice parameters. The time frame for this assignment did not allow for new climate scenario simulations to be produced.The results show that future winters will gradually, on average, have a smaller maximum ice extent compared to the control period (1975-2004). Ice seasons will also get shorter, with the largest differences in the southern areas. None of the scenarios yield ice free winters, and at least Bothnian Bay is expected to become fully ice covered on average, also during future winters. However, in the RCP8.5 scenario, ice with an average thickness of 10 cm or more disappears from the southern Bothnian Bay.In a 20-year perspective, changes in maximum ice extent are less distinct due to large inter-annual variations. In a 50-year perspective the change becomes more distinct and shows decreasing ice extents and smaller inter-annual variations.Level ice is expected to get thinner on average in all analysed areas, and the presence of heavily deformed ice is expected to decrease. However, models lack the ability to simulate brash ice barriers, which are formed when thin ice is pressed against a thicker ice edge or land by wind and waves. These types of barriers can be problematic for ships even in mild winters, and are expected to occur also in the future. Thinner and less dense ice fields also lead to increased ice drift in the Bothnian Bay and Bothnian Sea.The number of days with ice class based traffic restrictions for Swedish harbours are expected to decrease as sea ice thickness become thinner and ice seasons become shorter. The distribution of restrictions will also change, mainly in the Bothnian Bay where days with heavier ice classes (1A/B) decrease and days with lighter ice classes (1C/II) increase.Changes in maximum ice extent, length of ice season and average level ice thickness are judged to have a low uncertainty as the results are supported by both historical observations, and by the fact that model simulations are relatively close to the observations during the historical period. Changes in ice deformation, ice thickness distribution, and ice drift are judged to have a higher degree of uncertainty as there are no or very few observations to support model results.The study is partly limited by the lack of data for the lower RCP2.6 and by lacking analyses of possible changes in meteorological conditions. Another limiting factor is the relatively low number of regional climate model simulations with reliable ice parameters used in the study.