scholarly journals Retracing Hypoxia in Eckernförde Bight (Baltic Sea)

2021 ◽  
Author(s):  
Heiner Dietze ◽  
Ulrike Löptien
Keyword(s):  
Baltic Sea ◽  
Ocean Circulation ◽  
Circulation Model ◽  
Model Parameters ◽  
Monitoring Site ◽  
Minor Importance ◽  
Negative Consequences ◽  
Fish Kill ◽  
Bottom Waters ◽  
Oxygenated Water

Abstract. In recent years, upwelling events of low-oxygenated deep water have been repeatedly observed in Eckernförde Bight (EB) situated in the Baltic Sea, Germany. Many of these events were related to massive fish-kill incidents – with negative consequences for commercial fisheries and tourism. The aim of this study is to dissect underlying mechanisms and to explore the potential of existing monitoring programs to predict these events. Our main tool is an ultra-high spatially resolved general ocean circulation model which drives an elementary representation of the biogeochemical dynamics of dissolved oxygen (dubbed MOMBE and EckO2, respectively). In addition, we integrate artificial clocks that measure the residence time of the water in EB along with timescales of (surface) ventilation. We present an ensemble of hind cast model simulations, covering the period from 2000 up to 2018, designed to cover a range of poorly known model parameters for vertical background mixing (diffusivity) and local oxygen consumption within EB. Our results indicate that the dynamics of low (hypoxic) oxygen concentrations in bottom waters deep inside EB is, to first order, determined by the following antagonistic processes: (1) the inflow of low-oxygenated water from the Kiel Bight (KB) – especially from July to October and (2) the local ventilation of bottom waters by local (within EB) subduction and vertical mixing. Biogeochemical processes that consume oxygen locally, are apparently of minor importance for the development of hypoxic events. Reverse reasoning suggests that subduction and mixing processes in EB contribute, under certain environmental conditions, to the ventilation of the KB by exporting recently-ventilated waters enriched in oxygen. A detailed analysis of the 2017 fish-kill incident highlights the interplay between westerly winds importing hypoxia from KB and ventilating easterly winds which subduct oxygenated water. Finally, we explore the capabilities of – comparably computationally cheap – feed-forward artificial neuronal networks to forecast hypoxia deep in EB based on data at a monitoring site at the entrance of EB.

scholarly journals Retracing hypoxia in Eckernförde Bight (Baltic Sea)

2021 ◽  
Vol 18 (14) ◽  
pp. 4243-4264
Author(s):  
Heiner Dietze ◽  
Ulrike Löptien
Keyword(s):  
Dissolved Oxygen ◽  
Baltic Sea ◽  
Ocean Circulation ◽  
Quantitative Description ◽  
Circulation Model ◽  
Model Parameters ◽  
Monitoring Site ◽  
Minor Importance ◽  
Bottom Waters ◽  
Oxygenated Water

Abstract. An increasing number of dead zoning (hypoxia) has been reported as a consequence of declining levels of dissolved oxygen in coastal oceans all over the globe. Despite substantial efforts a quantitative description of hypoxia up to a level enabling reliable predictions has not been achieved yet for most regions of societal interest. This does also apply to Eckernförde Bight (EB) situated in the Baltic Sea, Germany. The aim of this study is to dissect underlying mechanisms of hypoxia in EB, to identify key sources of uncertainties, and to explore the potential of existing monitoring programs to predict hypoxia by developing and documenting a workflow that may be applicable to other regions facing similar challenges. Our main tool is an ultra-high spatially resolved general ocean circulation model based on a code framework of proven versatility in that it has been applied to various regional and even global simulations in the past. Our model configuration features a spacial horizontal resolution of 100 m (unprecedented in the underlying framework which is used in both global and regional applications) and includes an elementary representation of the biogeochemical dynamics of dissolved oxygen. In addition, we integrate artificial “clocks” that measure the residence time of the water in EB along with timescales of (surface) ventilation. Our approach relies on an ensemble of hindcast model simulations, covering the period from 2000 to 2018, designed to cover a range of poorly known model parameters for vertical background mixing (diffusivity) and local oxygen consumption within EB. Feed-forward artificial neural networks are used to identify predictors of hypoxia deep in EB based on data at a monitoring site at the entrance of EB. Our results consistently show that the dynamics of low (hypoxic) oxygen concentrations in bottom waters deep inside EB is, to first order, determined by the following antagonistic processes: (1) the inflow of low-oxygenated water from the Kiel Bight (KB) – especially from July to October – and (2) the local ventilation of bottom waters by local (within EB) subduction and vertical mixing. Biogeochemical processes that consume oxygen locally are apparently of minor importance for the development of hypoxic events. Reverse reasoning suggests that subduction and mixing processes in EB contribute, under certain environmental conditions, to the ventilation of the KB by exporting recently ventilated waters enriched in oxygen. A detailed analysis of the 2017 fish-kill incident highlights the interplay between westerly winds importing hypoxia from KB and ventilating easterly winds which subduct oxygenated water.

scholarly journals Effects of surface current/wind interaction in an eddy-rich general ocean circulation simulation of the Baltic Sea

2016 ◽  
Author(s):  
H. Dietze ◽  
U. Löptien
Keyword(s):  
Baltic Sea ◽  
Ocean Circulation ◽  
Surface Waters ◽  
Algal Blooms ◽  
Circulation Model ◽  
Transport Processes ◽  
Surface Currents ◽  
Wind Effects ◽  
The Baltic Sea ◽  
The Baltic

Abstract. Deoxygenation in the Baltic Sea endangers fish yields and favours noxious algal blooms. Yet, vertical transport processes ventilating the oxygen-deprived waters at depth and replenishing nutrient-deprived surface waters (thereby fuelling export of organic matter to depth), are not comprehensively understood. Here, we investigate the effects of the interaction between surface currents and winds (also referred to as eddy/wind effects) on upwelling in an eddy-rich general ocean circulation model of the Baltic Sea. Contrary to expectations we find that accounting for current/wind effects does inhibit the overall vertical exchange between oxygenated surface waters and oxygen-deprived water at depth. At major upwelling sites, however, as e.g. off the south coast of Sweden and Finland, the reverse holds: the interaction between topographically steered surface currents with winds blowing over the sea results in a climatological sea surface temperature cooling of 0.5 K. This implies that current/wind effects drive substantial local upwelling of cold and nutrient-replete waters.

Model based assessment of drift and fate of marine micro plastics in the Baltic Sea

2021 ◽  
Author(s):  
Jens Murawski ◽  
Jun She ◽  
Vilnis Frishfelds
Keyword(s):  
Baltic Sea ◽  
Ocean Circulation ◽  
Particle Surface ◽  
Circulation Model ◽  
Plastic Pollution ◽  
The Baltic Sea ◽  
Sea Transport ◽  
Biofilm Growth ◽  
Model Based ◽  
The Baltic

<p>Marine micro plastic is a growing problem, because of its ability to accumulate in the environment. Reliable data of drift patterns and accumulation zones are required to estimate environmental impacts on natural protected areas, spawning areas and vulnerable habitats. H2020 project CLAIM (Cleaning Litter by developing and Applying Innovative Methods) uses model based assessments to improve the knowledge on marine pathways, sources and sinks of land emitted plastic pollution. The assessment follows a systematic approach, to derive reliable emission values for coastal sources, and to model drift and deposition pattern of micro plastics from multiple sources: car tyres, cosmetic products. A 3D modelling tool has been developed, that includes all relevant key processes, i.e. currents and wave induced transport, biofilm growth on the particle surface, sinking and sedimentation. Core engine is the HBM ocean circulation model, which has been set-up for the Baltic Sea in high resolution of 900m. Multi-years-studies (2013-2019) were performed to evaluate seasonal drift pattern and accumulation zones. Highest micro plastic concentrations were found in coastal waters, near major release locations, but transport related offshore pattern can be found as well. These follow the major pathways of deeper sea transport, but are controlled by the seasonal dynamic of biofilm growth and sinking. We introduce the model and all relevant key processes. Seasonal drift pattern are discusses in detail. Validation results in the Gulf of Riga and the Gulf of Finland provide an overview of the quality of the model to predict the distribution of micro plastics. The study includes the assessment of mitigation scenarios, of 30% micro plastic load reductions. The impacts on the ocean levels of micro plastic concentrations are studied in detail.  </p><p> </p><p> </p>

Modelling Nd-isotopes with a coarse resolution ocean circulation model: Sensitivities to model parameters and source/sink distributions

2011 ◽  
Vol 75 (20) ◽  
pp. 5927-5950 ◽  
Author(s):  
Johannes Rempfer ◽  
Thomas F. Stocker ◽  
Fortunat Joos ◽  
Jean-Claude Dutay ◽  
Mark Siddall
Keyword(s):  
Ocean Circulation ◽  
Circulation Model ◽  
Model Parameters ◽  
Ocean Circulation Model ◽  
Nd Isotopes ◽  
Coarse Resolution ◽  
Source Sink

scholarly journals Nemo-Nordic 2.0: Operational marine forecast model for the Baltic Sea

2021 ◽  
Author(s):  
Tuomas Kärnä ◽  
Patrik Ljungemyr ◽  
Saeed Falahat ◽  
Ida Ringgaard ◽  
Lars Axell ◽  
...  
Keyword(s):  
Sea Ice ◽  
Baltic Sea ◽  
Sea Level ◽  
Ocean Circulation ◽  
Circulation Model ◽  
Forecast Model ◽  
The Baltic Sea ◽  
Baltic Basin ◽  
The North ◽  
The Baltic

Abstract. This paper describes Nemo-Nordic 2.0, an operational marine forecast model for the Baltic Sea. The model is based on the NEMO (Nucleus for European Modelling of the Ocean) circulation model and the previous Nemo-Nordic 1.0 configuration by Hordoir et al. [Geosci. Model Dev., 12, 363–386, 2019]. The most notable updates include the switch from NEMO version 3.6 to 4.0, updated model bathymetry and revised bottom friction formulation. The model domain covers the Baltic and the North Seas with approximately 1 nautical mile resolution. Vertical grid resolution has been increased from 3 to 1 m in the surface layer. In addition, the numerical solver configuration has been revised to reduce artificial mixing to improve the representation of inflow events. Sea-ice is modeled with the SI3 model instead of LIM3. The model is validated against sea level, water temperature and salinity observations, as well as Baltic Sea ice chart data for a two-year hindcast simulation. Sea level root mean square deviation (RMSD) is typically within 10 cm throughout the Baltic basin. Seasonal sea surface temperature variation is well captured, although the model exhibits a negative bias of approximately −0.5 °C. Salinity RMSD is typically below 1.5 g/kg. The model captures the 2014 Major Baltic Inflow event and its propagation to the Gotland Deep. The skill analysis demonstrates that Nemo-Nordic 2.0 can reproduce the hydrographic features of the Baltic Sea.

scholarly journals Reducing the model-data misfit in a marine ecosystem model using periodic parameters and Linear Quadratic Optimal Control

2012 ◽  
Vol 9 (8) ◽  
pp. 10207-10239 ◽  
Author(s):  
M. El Jarbi ◽  
J. Rückelt ◽  
T. Slawig ◽  
A. Oschlies
Keyword(s):  
Optimal Control ◽  
Ocean Circulation ◽  
Marine Ecosystem ◽  
Circulation Model ◽  
Ecosystem Model ◽  
Model Parameters ◽  
Linear Quadratic ◽  
Linear Quadratic Optimal Control ◽  
Marine Ecosystem Model ◽  
Quadratic Optimal Control

Abstract. This paper presents the application of the Linear Quadratic Optimal Control (LQOC) method for a parameter optimization problem in a marine ecosystem model. The ecosystem model simulates the distribution of nitrogen, phytoplankton, zooplankton and detritus in a water column with temperature and turbulent diffusivity profiles taken from a three-dimensional ocean circulation model. We present the linearization method which is based on the available observations. The linearization is necessary to apply the LQOC method on the nonlinear system of state equations. We show the form of the linearized time-variant problems and the resulting two algebraic Riccati Equations. By using the LQOC method, we are able to introduce temporally varying periodic model parameters and to significantly improve – compared to the use of constant parameters – the fit of the model output to given observational data.

scholarly journals Effects of surface current–wind interaction in an eddy-rich general ocean circulation simulation of the Baltic Sea

Ocean Science ◽  
2016 ◽  
Vol 12 (4) ◽  
pp. 977-986 ◽  
Author(s):  
Heiner Dietze ◽  
Ulrike Löptien
Keyword(s):  
Baltic Sea ◽  
Ocean Circulation ◽  
Surface Waters ◽  
Algal Blooms ◽  
Circulation Model ◽  
Transport Processes ◽  
Surface Currents ◽  
Wind Effects ◽  
The Baltic Sea ◽  
The Baltic

Abstract. Deoxygenation in the Baltic Sea endangers fish yields and favours noxious algal blooms. Yet, vertical transport processes ventilating the oxygen-deprived waters at depth and replenishing nutrient-deprived surface waters (thereby fuelling export of organic matter to depth) are not comprehensively understood. Here, we investigate the effects of the interaction between surface currents and winds on upwelling in an eddy-rich general ocean circulation model of the Baltic Sea. Contrary to expectations we find that accounting for current–wind effects inhibits the overall vertical exchange between oxygenated surface waters and oxygen-deprived water at depth. At major upwelling sites, however (e.g. off the southern coast of Sweden and Finland) the reverse holds: the interaction between topographically steered surface currents with winds blowing over the sea results in a climatological sea surface temperature cooling of 0.5 K. This implies that current–wind effects drive substantial local upwelling of cold and nutrient-replete waters.

scholarly journals Nemo-Nordic 2.0: operational marine forecast model for the Baltic Sea

2021 ◽  
Vol 14 (9) ◽  
pp. 5731-5749
Author(s):  
Tuomas Kärnä ◽  
Patrik Ljungemyr ◽  
Saeed Falahat ◽  
Ida Ringgaard ◽  
Lars Axell ◽  
...  
Keyword(s):  
Sea Ice ◽  
Baltic Sea ◽  
Water Temperature ◽  
Sea Level ◽  
Ocean Circulation ◽  
Circulation Model ◽  
Sea Surface ◽  
Model Assessment ◽  
The Baltic Sea ◽  
The Baltic

Abstract. This paper describes Nemo-Nordic 2.0, an operational marine model for the Baltic Sea. The model is used for both near-real-time forecasts and hindcast purposes. It provides estimates of sea surface height, water temperature, salinity, and velocity, as well as sea ice concentration and thickness. The model is based on the NEMO (Nucleus for European Modelling of the Ocean) circulation model and the previous Nemo-Nordic 1.0 configuration by Hordoir et al. (2019). The most notable updates include the switch from NEMO version 3.6 to 4.0, updated model bathymetry, and revised bottom friction formulation. The model domain covers the Baltic Sea and the North Sea with approximately 1 nmi resolution. Vertical grid resolution has been increased from 3 to 1 m in the surface layer. In addition, the numerical solver configuration has been revised to reduce artificial mixing to improve the representation of inflow events. Sea ice is modeled with the SI3 model instead of LIM3. The model is validated against sea level, water temperature, and salinity observations, as well as Baltic Sea ice chart data for a 2-year hindcast simulation (October 2014 to September 2016). Sea level root mean square deviation (RMSD) is typically within 10 cm throughout the Baltic basin. Seasonal sea surface temperature variation is well captured, although the model exhibits a negative bias of approximately −0.5 ∘C. Salinity RMSD is typically below 1.5 g kg−1. The model captures the 2014 major Baltic inflow event and its propagation to the Gotland Deep. The model assessment demonstrates that Nemo-Nordic 2.0 can reproduce the hydrographic features of the Baltic Sea.

Application of a Global Discharge Model to Atmospheric Model Simulations in the BALTEX Region

1999 ◽  
Vol 30 (3) ◽  
pp. 209-230 ◽  
Author(s):  
Stefan Hagemann ◽  
Lydia Dümenil
Keyword(s):  
Climate Change ◽  
Baltic Sea ◽  
Land Surface ◽  
General Circulation ◽  
Overland Flow ◽  
Climate Model ◽  
Circulation Model ◽  
Global Scale ◽  
Model Parameters ◽  
Discharge Model

In this study, a hydrological discharge model is presented which may be applied as a tool to validate the simulation of the hydrologic cycle of atmospheric models that are used in climate change studies. It can also be applied in studies of global climate change to investigate how changes in climate may affect the discharge of large rivers. The model was developed for the application with the climate models used at the Max-Planck-Institute for Meteorology. It describes the translation and retention of the lateral waterflows on the global scale as a function of the spatially distributed land surface characteristics which are globally available. Here, global scale refers to the resolution of 0.5° and lower, corresponding to a typical average gridbox area of about 2,500 km2. The hydrological discharge model separates between the flow processes of overland flow, baseflow and riverflow. The model parameters are mainly functions of the gridbox characteristics of topography and gridbox length. The hydrological discharge model is applied to the BALTEX (Baltic Sea Experiment) region using input from an atmospheric general circulation model (ECHAM4) as well as from a regional climate model (REMO). The simulated inflows into the Baltic Sea and its sub-catchments are compared to observed and naturalized discharges. The results of this comparison are discussed and the simulated values of precipitation, surface air temperature and accumulated snowpack are compared to both observed data and surrogate data.

Sign in / Sign up

Export Citation Format

Share Document