ALBERT

Description: Within the context of the predicted and observed increase in droughts and floods with climate change, large summer floods are likely to become more frequent. These extreme events can alter typical biogeochemical patterns in coastal systems. The extreme Elbe River flood in June 2013 not only caused major damages in several European countries but also generated large-scale biogeochemical changes in the Elbe estuary and the adjacent German Bight. The high-frequency monitoring network within the Coastal Observing System for Northern and Arctic Seas (COSYNA) captured the flood influence on the German Bight. Data from a FerryBox station in the Elbe estuary (Cuxhaven) and from a FerryBox platform aboard the M/V Funny Girl ferry (traveling between Büsum and Helgoland) documented the salinity changes in the German Bight, which persisted for about 2 months after the peak discharge. The Elbe flood generated a large influx of nutrients and dissolved and particulate organic carbon on the coast. These conditions subsequently led to the onset of a phytoplankton bloom, observed by dissolved oxygen supersaturation, and higher than usual pH in surface coastal waters. The prolonged stratification also led to widespread bottom water dissolved oxygen depletion, unusual for the southeastern German Bight in the summer.

Description: The Coastal Observing System for Northern and Arctic Seas (COSYNA) was established in order to better understand the complex interdisciplinary processes of northern seas and the Arctic coasts in a changing environment. Particular focus is given to the German Bight in the North Sea as a prime example of a heavily used coastal area, and Svalbard as an example of an Arctic coast that is under strong pressure due to global change.The COSYNA automated observing and modelling system is designed to monitor real-time conditions and provide short-term forecasts, data, and data products to help assess the impact of anthropogenically induced change. Observations are carried out by combining satellite and radar remote sensing with various in situ platforms. Novel sensors, instruments, and algorithms are developed to further improve the understanding of the interdisciplinary interactions between physics, biogeochemistry, and the ecology of coastal seas. New modelling and data assimilation techniques are used to integrate observations and models in a quasi-operational system providing descriptions and forecasts of key hydrographic variables. Data and data products are publicly available free of charge and in real time. They are used by multiple interest groups in science, agencies, politics, industry, and the public.

Description: Within the context of predicted and observed increase in droughts and floods with climate change, large summer floods are likely to become more frequent. These extreme events can alter typical biogeochemical patterns in coastal systems. The extreme Elbe River flood in June, 2013 not only caused major damages in several European countries, but also generated large scale biogeochemical changes in the Elbe Estuary and the adjacent German Bight. Due to a number of well documented and unusual atmospheric conditions, the early summer of 2013 in Central and Eastern Europe was colder and wetter than usual, with saturated soils, and higher than average cumulative precipitation. Additional precipitation at the end of May, and beginning of June, 2013, caused widespread floods within the Danube and Elbe Rivers, as well as billions of euros in damages. The floods generated the largest summer discharge on record within the last 140 years. The high-frequency monitoring network in the German Bight available within the Coastal Observing System for Northern and Arctic Seas (COSYNA) captured the flood influence on the German Bight. Monitoring data from a FerryBox station in the Elbe Estuary (Cuxhaven) and from a FerryBox platform aboard the M/V Funny Girl Ferry (traveling between Büsum and Helgoland) documented the salinity changes on the German Bight, which persisted for about 2 months after the peak discharge. The flood generated a large influx of nutrients, dissolved and particulate organic carbon on the coast. These conditions subsequently led to the onset of a chlorophyll bloom within the German Bight, observed by dissolved oxygen supersaturation, and higher than usual pH in surface coastal waters. The prolonged stratification also led to widespread bottom water dissolved oxygen depletion, unusual for the south eastern German Bight in the summer.

Description: We describe FESOM-C, the coastal branch of the Finite-volumE Sea ice – Ocean Model (FESOM2), which shares with FESOM2 many numerical aspects, in particular its finite-volume cell-vertex discretization. Its dynamical core differs in the implementation of time stepping, the use of a terrain-following vertical coordinate, and the formulation for hybrid meshes composed of triangles and quads. The first two distinctions were critical for coding FESOM-C as an independent branch. The hybrid mesh capability improves numerical efficiency, since quadrilateral cells have fewer edges than triangular cells. They do not suffer from spurious inertial modes of the triangular cell-vertex discretization and need less dissipation. The hybrid mesh capability allows one to use quasi-quadrilateral unstructured meshes, with triangular cells included only to join quadrilateral patches of different resolution or instead of strongly deformed quadrilateral cells. The description of the model numerical part is complemented by test cases illustrating the model performance.

Description: The dataset contains temperature, salinity, oxygen saturation, chlorophyll A and turbidity data from the AWIPEV underwater observatory from the year 2012 in a temporal resolution of 1 hour. The cabled observatory is located in 12m water depth and comprises single or multiple sensors for a specific parameter (see https://www.awi.de/en/science/biosciences/shelf-sea-system-ecology/main-research-focus/cosyna/underwater-node-spitsbergen.html) For a detailed description of the data see associated metadatafile "metadata_svulobs_2012_hydrography.pdf".

Description: The dataset contains temperature, salinity, oxygen saturation, chlorophyll A and turbidity data from the AWIPEV underwater observatory from the year 2018 in a temporal resolution of 1 hour. The cabled observatory is located in 12m water depth and comprises single or multiple sensors for a specific parameter (see https://www.awi.de/en/science/biosciences/shelf-sea-system-ecology/main-research-focus/cosyna/underwater-node-spitsbergen.html) For a detailed description of the data see associated metadatafile "metadata_svulobs_2018_hydrography.pdf".

Description: The dataset contains temperature, salinity, oxygen saturation, chlorophyll A and turbidity data from the AWIPEV underwater observatory from the year 2017 in a temporal resolution of 1 hour. The cabled observatory is located in 12m water depth and comprises single or multiple sensors for a specific parameter (see https://www.awi.de/en/science/biosciences/shelf-sea-system-ecology/main-research-focus/cosyna/underwater-node-spitsbergen.html) For a detailed description of the data see associated metadatafile "metadata_svulobs_2017_hydrography.pdf".

Description: The dataset contains temperature, salinity, oxygen saturation, chlorophyll A and turbidity data from the AWIPEV underwater observatory from the year 2016 in a temporal resolution of 1 hour. The cabled observatory is located in 12m water depth and comprises single or multiple sensors for a specific parameter (see https://www.awi.de/en/science/biosciences/shelf-sea-system-ecology/main-research-focus/cosyna/underwater-node-spitsbergen.html) For a detailed description of the data see associated metadatafile "metadata_svulobs_2016_hydrography.pdf".

Description: The dataset contains temperature, salinity, oxygen saturation, chlorophyll A and turbidity data from the AWIPEV underwater observatory from the year 2014 in a temporal resolution of 1 hour. The cabled observatory is located in 12m water depth and comprises single or multiple sensors for a specific parameter (see https://www.awi.de/en/science/biosciences/shelf-sea-system-ecology/main-research-focus/cosyna/underwater-node-spitsbergen.html) For a detailed description of the data see associated metadatafile "metadata_svulobs_2014_hydrography.pdf".