ALBERT

Description: Rivers are suspected to be a main suppliers of greenhouse gases (methane and carbon dioxide) to coastal seas, while the role of the interjacent tidal flats is still ambiguous. In this study we investigated the role of the Elbe and Weser estuaries as source of methane to the North Sea. We used high spatially resolved methane measurements from an underway degassing system and subsequent analysis with cavity ring down spectroscopy. Thus, a high-resolution representation of the methane distribution in surface waters as well as of hydrographic parameters was obtained for several cruises with two ships in 2019. For most areas, riverine methane was simply diluted by seawater, overlain by a strong tidal signal. However, on several occasions unexpectedly high methane concentrations were observed. Further detailed analysis will elucidate the role of riverine versus tidal impact on coastal North Sea methane fluxes.

Description: Regional models help to significantly improve our understanding of the global and regional cycles of, for example, carbon and nutrients. However, regional models often poorly resolve estuarine dynamics and are rather controlled by open boundary conditions. To investigate ecosystem processes in the south-eastern North Sea and Elbe estuary while avoiding the problems associated with nesting solutions we developed and applied an unstructured-mesh physical ocean model (FESOM-C). The FESOM-C model employs mixed unstructured-mesh methods and a finite - volume discretization. It is based on three-dimensional primitive equations for momentum, continuity, and density constituents. Vertically, the model uses a σ-coordinate system. The unstructured grid consists of quads and triangles zooming into the estuary, its vicinity and the coastline. Decrease in horizontal resolution provides a better numerical representation of coastal processes like asymmetries in tidal and residual flows, and periodic stratification. The lower resolution in the open sea allows conducting comparatively large regional studies. We developed a construction methodology for model setups in regions with complex coastal lines, including mixed mesh and bathymetry generation, open boundary and initial conditions and rivers distribution formation. The newly developed FESOM-C model could reproduce both barotropic and baroclinic dynamics of the coastal and estuary regions reasonably well. An Elbe summer flood event was well captured by the physical model. Investigation of flood event on ROFI of Elbe River were conducted with developed model by introduction of passive tracers in river outflow.

Description: Measuring environmental variables over longer times in coastal marine environments is a challenge in regard to sensor maintenance and data processing of continuously produced comprehensive datasets. In the project “MOSES” (Modular Observation Solutions for Earth Systems), this procedure became even more complicated because seven large Helmholtz centers from the research field Earth and Environment (E&E) within the framework of the German Ministery of Educatiopn and Research (BMBF) work together to design and construct a large scale monitoring network across earth compartments to study the effects of short-term events on long term environmental trends. This requires the development of robust and standardized automated data acquisition and processing routines, to ensure reliable, accure and precise data. Here, the results of two intercomparison workshops on senor accuracy and precicion for selected environmental variables are presented. Environmental sensors which were to be used in MOSES campaigns on hydrological extremes (floods and draughts) in the Elbe catchment and the adjacent coastal areas in the North Sea in 2019 to 2020 were compared for selected parameters (temperature, salinity, chlorophyll-A, turbidity and methane) in the same experimentally controlled water body, assuming that all sensors provide comparable data. Results were analyzed with respect to individual sensor accuracy and precision related to an “assumed” real value as well as with respect to a cost versus accuracy/precision index for measuring specific environmental data. The results show, that accuracy and precision of sensors do not necessarily correlate with the price of the sensors and that low cost sensors may provide the same or even higher accuracy and precision values as even the highest price sensor types.