Description: The presented work examines the carbonate system in the southern North Sea and its sensitivity to river input, anaerobic total alkalinity (TA) generation in the Wadden Sea and internal processes by using the ecosystem model ECOHAM. Furthermore, it is aimed to reproduce observations of high TA concentrations in the German Bight that could not be reproduced in former model studies. The study consists of three main parts that examine the TA production in the southern North Sea, the impact of riverine inputs on TA in the southern North Sea and the impact of TA and DIC exported from the Wadden Sea. The TA production in the southern North Sea was examined in the first main chapter. A prognostic treatment of TA was implemented into ECOHAM that enables the calculation of TA concentration changes due to the uptake and release of nutrients into the water column as well as calcification and decalcification. It was shown that the internal processes that produced TA irreversibly were mainly driven by the uptake of allochthonous nitrate and its subsequent denitrification. In the year 2008, about 76 Gmol TA yr-1 (228 mmol TA m-2 yr-1) was produced in the entire model domain (332,050 km²). Thereof, 13 Gmol TA yr-1 (221 mmol m-2 yr-1) were produced in the validation area (59,338 km²). TA production in shelf seas on annual scales was also derived from denitrification rates in former studies. Therefore, the internal turnover of TA calculated in the study at hand was compared to simulated denitrification in the validation area and in the whole model domain in 2008. A total amount of 80 Gmol N yr-1 (241 mmol N m-2 yr-1) was denitrified in the whole model domain, whereas 22 Gmol N yr-1 (370 mmol N m-2 yr-1) was denitrified in the southern North Sea. The deviation of denitrification from TA production was also examined for the years 1977 – 2009. Denitrification exceeded the TA production in the whole model domain / southern North Sea by 13 Gmol yr-1 / 11 Gmol yr-1 on average. Furthermore, it was shown that TA production correlates with nutrient supply from rivers in the southern North Sea but observed high TA concentrations could even not be reproduced in years with high river loads of TA. In the second main chapter it was examined whether observed high TA concentrations in the German Bight could originate from rivers. River loads of TA and DIC used in former studies were based on daily observations of freshwater discharge and on one concentration for TA and DIC for each river. Thus, these data lacked seasonal variability that can occur due to changes in riverine concentrations. Therefore, new data of river input of TA, DIC and nitrate were introduced for the main continental rivers. The level of TA concentration in the German Bight could be increased due to the increased loads of the river Rhine, but it was not possible to reproduce the observed high TA concentrations in the German Bight. Furthermore, the effective river load (Riveff) was introduced in this chapter in order to take freshwater discharges of rivers into account and to obtain a quantity that enables a comparison with TA production in the North Sea. As a result it was shown that concentration changes caused by river inputs in the German Bight were comparable with a TA consumption of 3 Gmol yr-1 in 2008. Thus, the effect of dilution due to freshwater discharge dominated there. This was in contrast to the Riveff of the river Rhine, which was comparable with a TA production of 24 Gmol TA yr-1. In the third main chapter the impact of Wadden Sea exchange rates of TA and DIC on concentrations in the German Bight was examined. Therefore, sources and sinks of TA and DIC were implemented into the model that indentified the dynamic behaviour of the Wadden Sea as an area of effective production and decomposition of organic material. The respective exchange rates were calculated by using measured pelagic DIC and TA concentrations in the Wadden Sea and modelled tidal water mass exchange. It was possible to bring the simulations significantly closer to observations in summer due to the implementation of the Wadden Sea. About 40 Gmol TA yr-1 were exported from the Wadden Sea into the North Sea, which was lower than the first estimate by Thomas et al. (2009) who calculated about 73 Gmol TA yr-1 originating from the Wadden Sea. Furthermore, the interannual variabilities of TA and DIC concentrations were examined for the years 2001 – 2009, which was mainly driven by hydrodynamic conditions. It was shown that the occurrence of weak meteorological blocking situations can lead to enhanced accumulation of simulated TA in the German Bight. In summary, it was found that the Wadden Sea was an important driver of the carbonate system variability in the southern North Sea. 68% of all TA concentration changes in the German Bight were caused by Wadden Sea export of TA, 23% were caused by the internal production of TA in the model and 9% caused by effective river loads.

Description: The coastal ocean is strongly affected by ocean acidification because of its shallow water depths, low volume, and the closeness to terrestrial dynamics. Earlier observations of dissolved inorganic carbon (DIC) and total alkalinity (TA) in the southern part of the North Sea, a northwest European shelf sea, revealed lower acidification effects than expected. It has been assumed that anaerobic degradation and subsequent TA release in the adjacent back-barrier tidal areas (Wadden Sea) in summertime is responsible for this phenomenon. In this study the exchange rates of TA and DIC between the Wadden Sea tidal basins and the North Sea and the consequences for the carbonate system in the German Bight are estimated using a 3D ecosystem model. The aim of this study is to differentiate the various sources contributing to observed high summer TA in the southern North Sea. Measured TA and DIC in the Wadden Sea are considered as model boundary conditions. This procedure acknowledges the dynamic behaviour of the Wadden Sea as an area of effective production and decomposition of organic material. According to the modelling results, 39 Gmol TA yr−1 were exported from the Wadden Sea into the North Sea, which is less than a previous estimate but within a comparable range. The interannual variabilities in TA and DIC, mainly driven by hydrodynamic conditions, were examined for the years 2001–2009. Dynamics in the carbonate system are found to be related to specific weather conditions. The results suggest that the Wadden Sea is an important driver for the carbonate system in the southern North Sea. On average 41 % of TA inventory changes in the German Bight were caused by riverine input, 37 % by net transport from adjacent North Sea sectors, 16 % by Wadden Sea export, and 6 % were caused by internal net production of TA. The dominant role of river input for the TA inventory disappears when focusing on TA concentration changes due to the corresponding freshwater fluxes diluting the marine TA concentrations. The ratio of exported TA versus DIC reflects the dominant underlying biogeochemical processes in the Wadden Sea. Whereas aerobic degradation of organic matter played a key role in the North Frisian Wadden Sea during all seasons of the year, anaerobic degradation of organic matter dominated in the East Frisian Wadden Sea. Despite the scarcity of high-resolution field data, it is shown that anaerobic degradation in the Wadden Sea is one of the main contributors of elevated summer TA values in the southern North Sea.

Description: The effect of satellite sea surface temperature assimilation on the forecast quality of the coastal ocean-biogeochemical model HBM-ERGOM in the North- and Baltic Seas is studied. The HBM-ERGOM model is currently used operationally without data assimilation by the German Federal Maritime and Hydrographic Agency (BSH). The model is configured with nested grids with a resolution of 5 km in the North- and Baltic Seas and a resolution of 900 m in the German coastal waters. The biogeochemical model ERGOM contains three phytoplankton groups (Cyanobacteria, Flagellates, Diatoms) and two zooplankton size groups to simulated the biogeochemical cycling in the coastal seas. To improve the predictions of the HBM-ERGOM model, data assimilation was added by coupling the model to the parallel data assimilation framework (PDAF, http://pdaf.awi.de). The ensemble-based error-subspace transform Kalman filter (ESTKF) is applied for the data assimilation. As a first step to improve the biogeochemical forecasts, before the planned assimilation of ocean color data products, the impact of assimilating satellite sea surface temperature data is assessed. Two cases are considered. First, the impact of weakly coupled data assimilation. In this case, the assimilation of temperature only directly influences the physical model variables in the analysis step while the biogeochemical fields react dynamically to the changed physical model state during the ensemble forecasts using the coupled model. The second case is the strongly-coupled data assimilation in which next to the physical model fields also the biogeochemical fields are directly updated in the analysis step through the multivariate covariances estimated by the joined physical-biogeochemical ensemble of model states. Here, it is assessed whether these covariances are sufficiently well estimated to result in an improvement of the biogeochemical fields.

Description: Data assimilation combines observational data with numerical simulation models. The methodology allos to improve the initialization of model predictions, determining model deficiencies, but also to enhance data sets by augmenting the data with dynamical information from numerical models simulating e.g. ocean physics or biogeochemistry. This combination can fill data gaps by an interpolation which accounts for the dynamical information provided by the numerical model. Further the observed information can be used to improve unobserved variables, and even fluxes. This is accomplished through the use of dynamically estimated cross-covariances between the observed and unobserved variables. The assimilation can result in data sets which, at the resolution of the model, exhibit smaller errors than using the observations or the model alone. I will discuss the method of ensemble-based data assimilation on the example of ocean-biogoechemical modeling with the assimilation of satellite ocean color data.

Description: Modellvorhersagen helfen die Datenbasis für die behördlichen Berichtspflichen für die Meeresstrategierahmenrichtlinie zu verbessern. Um die Qualität der Modellvorhersagen zu weiter zu verbessern kann der Modellzustand mit Beobachtungsdaten kombiniert werden. Dieses wird in quantitativer Weise durch Methoden der Datenassimilation vorgenommen. Im Rahmen des Projektes MeRamo wurde das Vorhersagemodell des Bundesamtes für Seeschifffahrt und Hydrographie für den kombinierten ozean-ökosystem Zustand in der Nord- und Ostsee mit Beobachtungsdaten des Satelliten Sentinel-3a sowie Satelliten der amerikanischen Behörde NOAA mit Hilfe der Datenassimilation kombiniert. Hierdurch wird die Simulation sowohl des physikalische Zustands (wie Temperatur und Salzgehalt) als auch ökologischer Größen wie Nährstoffe oder Planktonkonzentrationen beeinflusst. Im Vortrag wird die verwendete Datenassimilationsmethodik diskutiert und der Einfluss der Assimilation auf den Meereszustand, vor allem in Hinblick auf mögliche Indikatoren für die Meeresstrategierahmenrichtlinie betrachtet.

Description: The effect of the assimilation of satellite sea surface temperature onto the forecast quality of the coastal ocean-biogeochemical model HBM-ERGOM in the North and Baltic Seas is studied. The HBM-ERGOM model is currently used pre-operationally, without data assimilation, by the Germany Federal Maritime and Hydrographic Agency (BSH). The model is configured with nested grids with a resolution of 5km in the North and Baltic Seas and a resolution of 900m in the German coastal waters. To improve the predictions of the HBM-ERGOM model, data assimilation was added by coupling the model to the parallel data assimilation framework (PDAF, http://pdaf.awi.de). The ensemble-based local error-subspace transform Kalman filter (LESTKF) is applied for the data assimilation. It is studied how the biogeochemical model fields are impacted by the assimilation of sea surface temperature (SST) data from the Sentinel 3a and NOAA satellites. Two cases are considered. First, the impact of weakly coupled data assimilation. In this case, the assimilation of temperature only directly influences the physical model variables in the analysis step while the biogeochemical fields react dynamically to the changed physical model state during the ensemble forecasts using the coupled model. The second case is the strongly-coupled data assimilation in which next to the physical model fields also the biogeochemical fields are directly updated in the analysis step through the multivariate covariances estimated by the joined physical-biogeochemical ensemble of model states. Here, it is assessed whether these covariances are sufficiently well estimated to result in an improvement of the biogeochemical fields. For the weakly-coupled assimilation it is found that while the biogeochemical model fields are influenced by the SST data assimilation, the averaged deviation from in situ data remains almost constant and small improvements, but also deterioration, can occur. In case of the strongly coupled assimilation, the vertical effect of the assimilation has to be constrained to avoid deterioration. This effect is caused by the ensemble-estimated correlations between SST and biogeochemical fields in lower layers of the model.

Description: Satellite data of both physical properties as well as ocean colour can be assimilated into coupled ocean-biogeochemical models with the aim to improve the model state. The physical observations like sea surface temperature usually have smaller errors than ocean colour, but it is unclear how far they can also constrain the biogeochemical model variables. Here, the effect of assimilating satellite sea surface temperature into the coastal ocean-biogeochemical model HBM-ERGOM with nested model grids in the North and Baltic Seas is investigated. A weakly and strongly coupled assimilation is performed with an ensemble Kalman filter. For the weakly coupled assimilation, the assimilation only directly influences the physical variables, while the biogeochemical variables react only dynamically during the 12-hour forecast phases in between the assimilation times. For the strongly coupled assimilation, both the physical and biogeochemical variables are directly updated by the assimilation. The strongly coupled assimilation is assessed in two variants using the actual concentrations and the common approach to use the logarithm of the concentrations of the biogeochemical fields. In this coastal domain, both the weakly and strongly coupled assimilation are stable, but only if the actual concentrations are used for the strongly coupled case. Compared to the weakly coupled assimilation, the strongly coupled assimilation leads to stronger changes of the biogeochemical model fields. Validating the resulting field estimates with independent in situ data shows only a clear improvement for the temperature and for oxygen concentrations, while no clear improvement of other biogeochemical fields was found. The oxygen concentrations were more strongly improved with strongly coupled than weakly coupled assimilation. The experiments further indicate that for the strongly coupled assimilation of physical observations the biogeochemical fields should be used with their actual concentrations rather than the logarithmic concentrations.