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Warnemunde, Germany

The Leibniz Institute for Baltic Sea Research is a research institution located in Warnemünde , Germany.It is part of the Leibniz-Association, cooperates with the University of Rostock and was founded in 1992. Employing about 160 people the main focus lies on interdisciplinary study of coastal oceans and marginal seas, especially on Baltic Sea related oceanography. The institute is a follow-up of the former Institute of Oceanography which was part of the GDR Academy of Science.The institute is divided in four departments: physical oceanography, marine chemistry, biological oceanography, and marine geology. Central task of the institute is fundamental research but also teaching at the universities of Rostock and Greifswald. IOW has direct access to the research vessel "Maria S. Merian" and can access by request a variety of other medium-sized vessels for longer trips and interdisciplinary tasks from the German research fleet. The institute's facilities are financed by the German Federal Ministry of Education and Research, and the Ministry of Education of Mecklenburg-Western Pomerania. Wikipedia.


Burchard H.,Leibniz Institute for Baltic Sea Research | Hetland R.D.,Texas A&M University
Journal of Physical Oceanography | Year: 2010

This numerical modeling study quantifies for the first time the contribution of various processes to estuarine circulation in periodically stratified tidal flow under the impact of a constant horizontal buoyancy gradient. The one-dimensional water column equations with periodic forcing are first cast into nondimensional form, resulting in a multidimensional parameter space spanned by the modified inverse Strouhal number and the modified horizontal Richardson number, as well as relative wind speed and wind direction and the residual runoff. The along-tide momentum equation is then solved for the tidal-mean velocity profile in such a way that it is equated to the sum of the contributions of tidal straining (resulting from the temporal correlation between eddy viscosity and vertical shear), gravitational circulation (resulting from the depth-varying forcing by a constant horizontal buoyancy gradient), wind straining, and depth-mean residual flow (resulting from net freshwater runoff). This definition of tidal straining does not only account for tidal asymmetries resulting from horizontal buoyancy gradients but also from wind straining and residual runoff. For constant eddy viscosity, the well-known estuarine circulation analytical solution with polynomial residual profiles is directly obtained. For vertically parabolic and constant-in-time eddy viscosity, a new analytic solution with logarithmic residual profiles is found, showing that the intensity of the gravitational circulation scales with the horizontal Richardson number. For scenarios with realistic spatially and temporally varying eddy viscosity, a numerical water column model equipped with a state-of-the-art two-equation turbulence closure model is applied to quantify the individual contributions of the various processes to estuarine circulation. The fundamental outcome of this study is that, for irrotational flow with periodic stratification and without wind forcing and residual runoff, the tidal straining is responsible for about two-thirds and gravitational circulation is responsible for about one-third of the estuarine circulation, proportionally dependent on the horizontal Richardson number, and weakly dependent on the Strouhal number. This new and robust result confirms earlier estimates byH. Burchard and H. Baumert, who suggested that tidal straining is the major generation mechanism for estuarine turbidity maxima. However, a sensitivity analysis of the model results to details of the turbulence closure model shows some uncertainty with respect to the parameterization of sheared convection during flood. Increasing down-estuary wind straining and residual runoff reduce the quantitative contribution of tidal straining. For relatively small horizontal Richardson numbers, the tidal straining contribution to estuarine circulation may even be reversed by down-estuary wind straining. © 2010 American Meteorological Society. Source


Neumann T.,Leibniz Institute for Baltic Sea Research
Journal of Marine Systems | Year: 2010

The expected climate change is of growing interest on the regional scale, including the Baltic Sea. However, simulations with global models do not sufficiently resolve the regional impact. Consequently, dynamic downscaling methods are being used to convert the results obtained in global models to the regional scale. In the present study, two regional data sets for greenhouse gas emission scenarios, A1B and B1, for the period 1960 to 2100, were used to force transient simulations with a 3D ecosystem model of the Baltic Sea. The results showed that the expected warming of the Baltic Sea is 1-4 K, with a decrease in salinity and a much reduced sea-ice cover in winter. In addition, the season favoring cyanobacterial blooms is prolonged, with the spring bloom in the Northern Baltic Sea beginning earlier in the season, while the oxygen conditions in deep water are expected to improve slightly. © 2009 Elsevier B.V. All rights reserved. Source


The evasion of elemental mercury (Hg0) from water surfaces is a key process in biogeochemical mercury cycling. Knowledge of the Hg0 diffusion coefficient (DHg0) in water is essential for Hg0 water-air flux calculations, but no measured value has been available. In this study, DHg0was measured in pure water and in water of oceanic salinity within an environmental temperature range between 5°C and 30°C. A diffusion cell was constructed consisting of two chambers separated by an aqueous gel membrane allowing molecular diffusion only. The corresponding parameterizations were developed on the basis of the Eyring equation, which defines an activation energy (Ea) for the diffusion process. The temperature dependences of DHg0(in cm2 s-1) for freshwater, Dfresh Hg0 = 0:0335e-18:63 kJ mol-1/RT, and for seawater, Dsea Hg0 = 0:0335e-0:0011e-11:06 kJ mol-1/RT, with R the gas constant and T the temperature in Kelvin, were thus obtained with an error of ±15%. Whereas the measured Dfresh Hg0 was in good agreement with the theoretical proposals of a molecular dynamics (MD) simulation, Dsea Hg0 was clearly lower, probably because of the unaccounted effect of the polarization of mercury atoms in the salt solution, which hampers diffusion. In geochemistry applications, use of the newly determined Dsea Hg0 instead of the Dfresh Hg0 from MD simulations would have differential effects on determinations of mercury emissions from the world's oceans. The effect on the tropical ocean would be the largest, decreasing the Hg0 water-air flux estimate by 20%. Toward higher latitudes (~50°), the calculated emission would drop by about 10%. On the basis of a recent large data set, the estimated amount of mercury released by the Atlantic Ocean would decrease by approximately 17%. © 2014, by the Association for the Sciences of Limnology and Oceanography, Inc. Source


Feistel R.,Leibniz Institute for Baltic Sea Research
Desalination | Year: 2010

To the Gibbs function for seawater endorsed in 2008 by the International Association for the Properties of Water and Steam (IAPWS), an extension to higher temperature and salinity has been developed, based on density measurements at atmospheric pressure, temperatures up to 90 °C and absolute salinities up to 70 g/kg, as recently published by Millero and Huang (2009). In the range considered, the standard uncertainty in density of those data is less than 7 ppm. The new extension improves the applicability of the current standard formulation to hot seawater concentrates as encountered in desiccating seas or desalination plants, and maintains numerical consistency with most of the data used for the original formulation within their experimental uncertainties. Absolute salinity is expressed in the Reference-Composition Salinity Scale of 2008, temperature in the International Temperature Scale of 1990, ITS-90. © 2009 Elsevier B.V. All rights reserved. Source


Grawe U.,Leibniz Institute for Baltic Sea Research
Ocean Modelling | Year: 2011

Stochastic differential equations (SDEs) offer an attractively simple solution to complex transport-controlled problems, and have a wide range of physical, chemical, and biological applications, which are dominated by stochastic processes, such as diffusion. As for deterministic ordinary differential equations (ODEs), various numerical scheme exist for solving SDEs. In this paper various particle-tracking schemes are presented and tested for accuracy and efficiency (time vs. accuracy). To test the schemes, the particle tracking algorithms are implemented into a community wide used 1D water column model. Modelling individual particles allows a straightforward physical interpretation of the involved processes. Further, this approach is strictly mass conserving and does not suffer from the numerical diffusion that plagues grid-based methods. Moreover, the Lagrangian framework allows to assign properties to the individual particles, that can vary spatially and temporally. The movement of the particles is described by a stochastic differential equation, which is consistent with the advection-diffusion equation. Here, the concentration profile is represented by a set of independent moving particles, which are advected according to the velocity field, while the diffusive displacements of the particles are sampled from a random distribution, which is related to the eddy diffusivity field. The paper will show that especially the 2nd order schemes are accurate and highly efficient. At the same level of accuracy, the 2nd order scheme can be significantly faster than the 1st order counterpart. This gain in efficiency can be spent on a higher resolution for more accurate solutions at a lower cost. © 2010 Elsevier Ltd. Source

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