Scenario simulations of recent Baltic Sea inflows using the hydrodynamic transport model GETM

A. K. Stips1, K. Bolding2, M. Lilover1,3

1Joint Research Centre Via E. Fermi, TP272 I-21027 Ispra, Italy

2Bolding&Burchard Hydrodynamics Strandgyden 25

DK-5466 Asperup, Denmark 3Marine Systems Institute

Akadeemia tee 21 12618 Tallinn, Estonia

Abstract-The aim of the present study is to simulate larger salt water inflows from the North Sea into the Baltic Sea reaching the Gotland Deep with the GETM (http://getm.eu) hydrodynamical model. Specifically we want to test the influence of different model settings, different initial conditions and a variety of forcing conditions on the occurrences of salt water inflows. The model area covers the whole Baltic Sea and North Sea, therefore no prescribed sealevel forcing in the Kattegat area is applied. Initial conditions and 3D boundary conditions are derived from climatological data [10]. The tidal forcing at the open boundaries in the English Channel and the open North Sea are constructed from 13 partial tides taken from the TOPEX/POSEIDON harmonical tide analysis. Relatively coarse meteorological forcing available from ECMWF re-analysis data was used and seems to be of sufficient spatial resolution in order to reproduce the main features of the inflow dynamics during recent years. For the river inflow we used climatological data for the 30 most important rivers within the model area. It can be demonstrated, that the basic dynamics of sea level variations in that area is already reproduced by forcing the model with such low resolution meteorological data (0.5o*0.5o). Also the main characteristics of bottom and surface salinity are most of the time simulated sufficiently well.

Further we are able to show, that for the larger events the inflowing salt water from the Belt Sea is also progressing in the simulations until it reaches the Gotland Deep. Finally we compare the modeled scenarios of the 2002 and 2003 inflows with measured data. From that we try to identify the most important criteria that allow salt water inflows to occur and we try to better assess the range of uncertainty.

I. INTRODUCTION

The Baltic Sea is a salinity stratified semi-enclosed basin located in Northern Europe. The salinity stratification is maintained by the surface freshwater supply from rivers and precipitation and by the bottom inflow of high saline water from the North Sea. Until recently it was believed that the bottom water in the deep sub-basins is only replaced after large storm forced inflow events, so called Major Baltic Inflows (MBIs, [1]). The importance for the renewal of intermediate layers in the halocline of small and medium strength baroclinic inflows has been demonstrated by [2]. Reference [3] have shown, that during the past 2 decades the frequency of large barotropic inflows has decreased, whereas the frequency of medium intensity baroclinic inflows has increased.

Many different factors are influencing the water exchange between the North Sea and the Baltic Sea and specifically the inflow of salty and oxygen rich water to the deeper Baltic basins like the Gotland Sea. These factors comprise the large scale air pressure fields over the entire area, the resulting wind fields specifically in the channel area, the fresh water run off to the Baltic Sea, water level (filling state) of the Baltic Sea, tides, the exact bathymetry determining the cross sectional area and the related bottom friction as well as the vertical and horizontal mixing processes which are diluting the inflowing water masses.

Conceptual models [4] and [5] could qualitatively show that the two major factors determining the occurrence of MBIs are the filling state of the Baltic Sea (as measured by the Landsort sealevel) and the large scale pressure field over the North Sea and Baltic Sea area which determine the barotropic pressure gradient. Only recently the smaller but nevertheless important role of the baroclinic pressure gradient in driving small salt water inflows was experimentally discovered by [6].

Contrary to the general understanding of the main processes achieved, until recently the detailed 3D hydrodynamic modeling of salt water inflows was not completely satisfactory. In most known published model studies and in many personal communications it was shown that despite the adequate reproduction of the general features the inflowing salt water along its way through the different basins (from the Belt Sea via Arkona Sea, Bornholm Sea into the Gotland Sea) became too diluted and therefore lost its density and finally could not enter in sufficient amounts or not deep enough into the Gotland Basin.

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As the main reason for this dilution process an unrealistically high numerical diffusion of current state of the art models is suspected. Depending on the characteristics of the model used there are at least two different reasons proposed for the occurrence of this excessively high mixing: firstly artificial mixing at the step like bottom topography for z-coordinate models and secondly pressure gradient errors for σ-coordinate models.

Despite the fact that this problem has been known for many years and is investigated by several different research groups extended and systematic studies of the importance of the different factors influencing the salt water inflow to the Baltic Sea have not been done. Even very fundamental questions about the role of the local wind field in driving or preventing salt inflows to the Baltic proper have not been well investigated. Here we will present a first attempt to separate the importance of the different processes and parameters. For doing that we are applying the public domain General Estuarine Transport Model (GETM, [7], getm.eu), which had been used successfully for performing realistic simulations [8].

II. MODEL IMPLEMENTATION

A. General features GETM solves the three-dimensional hydrostatic equations of motion by applying the Boussinesq approximation and the eddy

viscosity assumption. Subgrid scale mixing is parameterized using a turbulence closure with flux boundary conditions. The turbulence scheme for vertical mixing in GETM is chosen via the GOTM (www.gotm.net) turbulence model. In this study we applied the standard k-ε turbulence closure. A simple parameterization for considering the additional mixing effect of breaking internal waves is included. The model allows the application of different schemes for vertical as well as for horizontal coordinates.

Different numerical schemes for tracer advection are implemented and can be used. For this study we mainly used the ULTIMATE quickest algorithm, but we also compared to flux corrected (FCT) scheme. A background harmonic diffusion of AH=10 m2s-1 is applied.

For details of the model the reader is referred to [7].

B. Implementation details The GETM model was implemented for the coupled North Sea Baltic Sea area using different grid sizes of 6 nm, 3 nm and

2’x3’ applying cartesian and spherical coordinate systems respectively. These grids have been generated from different sources of bathymetric data, comprising the DYNOCS bathymetry, the IOWTOPO data [9] and the GEBCO global 1’ topographic data set. Further different filters were applied for smoothing the bathymetry, as this is required for terrain following coordinates which have been used for these simulations. As an example the 3 nm bathymetry generated in such a way is shown in Fig. 1, which also provides an impression of the model area. It should be mentioned that the difficulty of simulating salt water inflows using such a large coupled domain is considerably increased, as the very important Kattegat water level which is determining the barotropic pressure gradient cannot be prescribed.

The barotropic time step had to be adjusted to the respective horizontal resolution. The split factor between barotropic and baroclinic mode was 30. Open boundaries of the model domain are existing between the North Sea and the North Atlantic and the English Channel. Climatological river runoff from 33 major rivers was used for the fresh water input. The model was initialized using the climatological temperature and salinity data compiled by [10]. For the open boundary conditions at the Atlantic these climatological data were also applied via a sponge layer formulation. Meteorological forcing data were provided by the European Centre for Medium Range Weather Forecasting (ECMWF, www.ecmwf.int). The following basic data were extracted from the ECMWF data base: air pressure, air temperature, total cloud cover, wind speed (east and north component), dew point temperature, precipitation and evaporation. The time step of the data is 6 hours and the spatial resolution is approximately 0.5 degrees. The data are interpolated in space and time to the respective model grid.

For the tidal forcing at the open boundaries the parameterization derived from the TOPEX-POSEIDON data set has been used, see podaac.jpl.nasa.gov/cdrom/tide. The extracted data are linearly interpolated in time and space to the open boundary elevation points.

C. Scenario simulations The main characteristics of the simulations here presented are summarized in Table 1. The standard setup (Run0, r0) used 30

vertical layers, fresh water flux (FWF) from rivers and from the atmosphere, tidal forcing at the open boundaries, complete meteorological surface forcing and a smoothed bathymetry. For the calculation of the internal pressure gradient (IP) the Blumberg-Mellor scheme [11] was used. For the different scenarios (run1 to run9 here) selected forcings or other features were deactivated, to assess their relative importance to the overall quality of the simulation. For run r4 the number of vertical layers was reduced to 15.

Fig. 1 Bathymetry

TABLE I CHARACTERISTICS OF THE PERFORMED SCENARIO SIMULATIONS

Forcing Start year Comments

Run00 (r0) FWF, rivers, tides, wind, air pressure, smoothed, 30L 1986 Standard

Run01 (r1) FWF, no rivers, tides, wind, air pressure, smoothed, 30L 1997

Run02 (r2) FWF, rivers, no tides, wind, air pressure, smoothed, 30L 1997

Run03 (r3) FWF, rivers, tides, wind, air pressure, unsmoothed, 30L 1997

Run04 (r4) FWF, rivers, tides, wind, air pressure, smoothed, 15L 1997

Run05 FWF, rivers, tides, no wind, air pressure, smoothed, 30L 1997

Run06 FWF, rivers, tides, wind, no air pressure, smoothed, 30L 1997

Run07 FWF, rivers, tides, wind, air pressure, smoothed, 30L 1997 Different IP scheme

Run08 FWF, rivers, tides, wind, air pressure, smoothed, 30L 1997 Different IP scheme

Run09 (r9) No FWF, rivers, tides, wind, air pressure, smoothed, 30L 1986

III. RESULTS

D. Influence of wind forcing

Fig. 2 Salinity distribution along the Baltic Sea monitoring section in simulation with wind forcing (left) and without wind

forcing (right) One question that is often asked but which cannot be answered by nature experiments is “what is the influence of the typical

wind forcing for the water exchange between Baltic Sea and North Sea?” To give a qualitative answer to this question, we ran the coupled setup for the second half of 2002, when the exceptional warm summer inflow occurred [2,6], using an identical setup, but once with the wind forcing from ECMWF and once without wind forcing. The salinity distribution along a section from the entrance area via the different basins into the Gotland deep (240 m) during the unusually warm summer inflow in 2002 is presented in Fig 2. Darker colors indicate higher salinity.

The left hand side of Fig. 2 shows the normal picture of the already rather diluted salt water plume just arriving in the Gotland Sea in October 2002. This arrival time of the inflow in the Gotland Sea, which started in the beginning of August 2002 with inflow from the Great Belt is confirmed by observations of [12]. Therefore we can say that the model reproduces well the summer inflow. Further this clearly shows that the main forcing for this inflow is the baroclinic pressure gradient. As might be expected, the simulation without wind forcing maintains a much stronger vertical stratification along the section. This is resulting in a stronger baroclinicity and therefore giving an increased inflow of salt water into the Gotland deep. Actually these higher bottom salinities are changing the simulations to be in better agreement with the observations. This qualitative behavior of the two runs points to the fact that the model internal mixing could be too high.

E. Multi-annual runs In Fig. 3 the bottom salinity for the central Gotland Basin station (BY15) is plotted over time for some selected model runs as

described in Table 1. The runs usually extend from year 1998 until end of 2007, some runs were initialized from climatology in January 1997, whereas some runs were started already in 1986.

The simulation r0 (black dots), starting from climatology represents a basic reference run. During the first year (1997) the model has to adapt to the artificial initial density stratification taken from the climatological data. During the first phase of this process the salinity is decreasing at an unrealistically high rate, resulting from strong exchange processes. This adaptation process seems to last about one year. At the end of the first year the salinity has approached to the original starting value again. Compared to the measured bottom salinities from the Baltic monitoring program (upper bold dots) the climatological data are about 2 PSU too small. Therefore using such climatological data we cannot expect to perform realistic hind casts of the measured bottom salinity here. Nevertheless most well known minor inflow events can be detected by salinity peaks in the time series (winter 2000, summer 2001, fall 2002, winter 2003).

The expected high importance of the riverine fresh water input not only for the surface salinity, but also for the bottom salinity is evidenced by run r1 (dotted line). The bottom salinity increases after the usual initial drop in almost all the years, with a rate of

3PSU in 10 years. It is therefore clear that the usage of the best available river runoff data is essential for adequately simulating the Baltic Sea salinity.

The role of tides in the Baltic Sea is considered to be small and as can be seen in Fig. 3 the run r2 (dashed line) using no external tidal forcing is only slightly different from r0. The salinities are increased about 0.2-0.4 PSU when switching the tidal forcing off, but have a tendency to increase further (increase about 0.5 PSU in 10 years). This underlines the fact that despite the small influence of tidal mixing in the Baltic proper, it cannot be ignored for long term (decadal) simulations.

General vertical coordinates as used in this study are terrain following and therefore allow a good representation of dense water inflows [13], whereas special measures must be applied to achieve equally good results in z-level models [14]. Unfortunately the disadvantage of using terrain following coordinates is increased artificial mixing due to numerical errors in the calculation of the internal pressure gradient of steep topography [15]. Therefore the realistic rough bottom topography is usually smoothed before doing simulations with terrain following models. Not applying the normal smoothing will lead to increased mixing in the model domain and therefore the salinities are reduced, as can be seen in Fig. 3 run r3 (+-+ line). Actually a very similar net effect is achieved by reducing the overall number of vertical layers from 30 layers to 15 layers, as in run r4 (diamonds). Again the salinities are reduced by about 0.2-0.3 PSU compared to the run r0 using 30 layers.

Finally we present here results from the run r9 (asterisks), which uses an identical setup compared to the standard run r0, except that is was started already in January 1986 and continued until end of 2007 and that no FWF over the sea surface is considered. River runoff is still included. As the Baltic Sea area has net precipitation an increased salinity could be expected. Indeed in January 1998, when our comparison starts, the salinity of r9 is about 1PSU higher than in run r0 and thus more close to reality. But during the following 10 years the salinity decreases and approaches that of r0 and shows much less variability than in the reference run. The reason for this remains unclear, but it has to be considered that the FWF component as it is provided from atmosphere models is still the model forcing component with the highest uncertainty.

IV. CONCLUSIONS

An attempt was made to investigate some of the factors that influence the quality of multi-annual simulations of the complicated large scale estuarine basin like Baltic Sea. Despite the fact that many studies have dealt with the circulation in the Baltic Sea experimentally or by simulation, there are still many open questions related to the pathways of the inflowing salt water in the various sub basins. The role of upwelling stirred by the topography and of diapycnal mixing caused by breaking internal waves is still not understood. Here we were able to show the critical importance of applying realistic fresh water fluxes and tidal forcing for achieving improved simulations. The smoothing of the topography reduces artificial mixing in the model but on the

Fig. 3 Simulated bottom salinity in the Gotland Deep

other hand compromises the strength of the inflow events by reducing the amount of inflowing water as well as some circulation features. It seems to be necessary to significantly improve current hydrodynamic models to achieve more realistic simulations. One way in this direction might be to introduce so called adaptive coordinates [16], which could avoid some of the major drawbacks of currently used coordinate systems.

ACKNOWLEDGMENT

We thank the GETM development team for their continuous enthusiasm and support in helping to improve and to run the model. The measured data for this study were provided by the Baltic NEST database. Excellent informatics support was given by Philippe Simons and Francesco Andreozzi.

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