Numerical models are required to estimate ocean state variables at times and locations for which observations are not available. Of particular importance for the COSYNA project is the ability to provide forecasts of different parameters concerning ocean waves, circulation, and suspended matter. The combination of models covering different processes and spatial scales provides a comprehensive picture of the physical and biogeochemical ocean state of the German Bight.
Three-dimensional distribution of water temperatures computed with a numerical model. The data are co-located with Scanfish measurements taken between 28 Juli and 5 August 2009.
The nested-grid pre-operational circulation model consists of three model configurations: (1) Coarse-resolution outer model for the North Sea-Baltic Sea (grid size about 5 km), (2) fine-resolution inner model (grid size about 0.8 km) covering the German Bight, (3) very fine-resolution model for the Wadden Sea region (grid size about 200 m) resolving the barrier islands and the tidal flats. Although the simulation of features such as vertical stratification is very complex, the model is in good agreement with observations (figure below).
Simulated wave heights in the German Bight (21 April 2010)
The grid-nested COSYNA wave model system provides 24-hour wave forecasts twice a day on a regional scale for the North Sea and on a local scale for the German Bight. Wind fields and boundary information provided by the German Weather Service (DWD) force the forecast runs delivering a number of wave parameters such as wave height, period and direction. As example, the wave heights on 21 April, 2010 show in the German Bight at midnight (below) a typical distribution with low values at the coast and higher values off shore.
Typical distribution of modelled SPM concentrations (improved by assimilated satellite data) in mg/l at the sea surface (22 March 2003, 10:20).
The distribution of suspended particulate matter (SPM) is of primary importance for the ecological status of the sea because it impedes the daylight penetration into deeper water layers and affects the accumulation of pollutants. The model takes into account advection, vertical exchange processes due to currents and waves, sedimentation, re-suspension, and erosion at the bottom, as well as bioturbation in the sediment.
Biogeochemical cycling of matter is characterized by the interaction of physical, chemical and biological processes. Its complexity is enhanced in shallow coastal waters due to a tight coupling of processes in sediments and the water column. Biogeochemical interactions, with various feedback loops, entail highly dynamic carbon, nitrogen, and phosphorus mass fluxes that can be estimated with biogeochemical models.
The Model for Adaptive Ecosystems in Coastal Seas (MAECS) resolves the dynamics of nutrients, phytoplankton, zooplankton, dissolved organic matter, and detritus. Its novelty is the focus on adaptation in the biota, including aspects such as size-selective grazing by zooplankton or photo-acclimation of algae, expressed by variations in the chlorophyll-to-carbon (Chla:C) ratio. MAECS is coupled to the physical General Estuarine Transport Model GETM. In the present version, observations are used to calibrate model parameterisations and to validate the model under a range of boundary conditions. COSYNA observations provide important constraints for flux estimation and magnitudes of spatial and temporal variability. On a longer-term, the assimilation of data into MAECS will improve state estimation, delivering reliable forecasts of ecosystem key-state variables.
Chla/C ratio: Surface distribution of Chla:C (gChla/gC) from the shallow Wadden Sea towards the central German Bight.
Two examples of model results are presented in the figures. First, the models ability to resolve physiological variations of the phytoplankton’s cellular Chla:C ratio is relevant when relating actual nitrogen biomass to observed chlorophyll concentrations. Patterns identify regions with enhanced chlorophyll synthesis, compensating for reduced light availability, e.g., due to deeper mixing or increased light attenuation.
Particulate organic detritus: Bottom concentration of organic detritus (carbon, nitrogen and phosphorus converted to total mass (mg/l) representing the organic fraction of SPM).
Second, growth of phytoplankton (“primary production”) and the exudation of polysaccharides control the coagulation and settling behaviour of suspended matter. Patterns can reflect regions with enhanced aggregation and sinking of algae, exporting organic matter to the sediments.