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 heavily used German Bight in the North Sea. The automated observing and modelling system is designed to monitor real-time conditions, to provide short-term forecasts and data products, and to assess the impact of anthropogenically induced change.

We investigated how the largest seabird of the North Atlantic, the northern gannet, uses the southern North Sea as its habitat to search for food. We deployed small GPS trackers on the birds that recorded the birds' movements in detail. Birds were away from the breeding colony mostly for 1–15 h and up to 80 km distance to find prey for their chicks and themselves. To obtain food, they dove frequently to depths of 1–3 m, with a maximum of 11 m.

We observed oceanographic and community data from October 2013 to November 2014 in the shallow waters of Kongsfjorden on the western coast of Svalbard (Norway) using remote controlled hydrographic and optic sensors. Daily vertical profiles of temperature, salinity, and turbidity were sampled together with stereo images of the macrobiotic community, including fish. A distinct seasonal cycle in total species abundances was found with surprisingly high animal counts during the polar winter.

COSYNA (Coastal Observing System for Northern and Arctic Seas) pursued various activities for stakeholder interaction. The steps, e.g. initial survey, external evaluation, interviews and workshops with stakeholders from the offshore wind sector, are integrated into the COSYNA product life cycle outlined here and exemplified for the product Surface Current Fields. By sharing first-hand experiences this study contributes to the emerging knowledge on integration of coastal research and end users.

The significant wave height (Hs) is one of the most relevant parameters to describe a sea state statistically. This parameter is commonly monitored by measurement devices placed in the water (wave rider buoy, ADCP), which require expensive maintenance. In this study, X-band radar, generally used for ship navigation, was modified to measure water particle speeds using the Doppler effect. Based on the obtained data, a simple method is introduced to remotely estimate Hs with a reasonable accuracy.

This study focuses on how the June 2013 Elbe River flood affected the southern German Bight. The largest summer flood within the last 140 years, it generated a substantial plume of nutrient-rich, buoyant waters from the Elbe estuary onto the coast. During the calm 2013 summer, the flood was followed by prolonged (2-month) water column stratification, chlorophyll blooms in surface, and uncharacteristically low oxygen in bottom waters. With climate change, these events are becoming more frequent.

The use of ocean gliders, a class of underwater vehicles for observing the ocean to understand biogeochemical and physical processes, has been pioneered in the North Sea as part of the coastal observatory COSYNA. Since gliders go slow, strong tidal currents are problematic for their navigation. To predict (< 12 h) and reconstruct the local currents and the actual transect under water to know where the measurements were actually taken, an algorithm was developed using glider data only.

Ripples are small regular sand waves found on beaches or the floor of rivers and coastal seas. Their shapes and dimensions are controlled by properties of the sand and the strength of waves and currents. The form of ripples can be predicted by mathematical formulas which were often developed from laboratory experiments. In this work, we present methods for measurement of ripple heights and lengths from the North Sea and compare the results to calculated dimensions.

Here we introduce a new molecular-based observation strategy for high-resolution assessment of marine microbes (e.g., microalgae) in space and time. The observation strategy combines automated sampling on board ships or observation platforms with a variety of different molecular genetic methods for refined observation of marine microbes at adaquate scales, in order to better understand the impact of climate change on this group of organisms, which are at the base of marine food webs.

We compared observations from the operational Time Series Station Spiekeroog, related to water transparency, conducted correlation tests among these measured parameters, and explored the utility of both acoustic and optical tools in monitoring water transparency. Our findings suggest that both optical and acoustic measurements can be reasonable proxies of water transparency with the potential to mitigate gaps and increase data quality in long-time observations of marine environments.

This paper describes coastal ocean forecasting practices exemplified for the North Sea and Baltic Sea. It identifies new challenges, most of which are associated with the nonlinear behavior of coastal oceans. It describes the assimilation of remote sensing, in situ and HF radar data, prediction of wind waves and storm surges, as well as applications to search and rescue operations. Seamless applications to coastal and estuarine modeling are also presented.

We investigated sinking velocity (w_s) of suspended particulate matter (SPM) in the German Bight. By inferring w_s indirectly from an extensive turbidity data set and hydrodynamic model results, we found enhanced w_s in a coastal transition zone. Combined with known residual circulation patterns, this led to a new conceptual understanding of the retention of fine minerals and nutrients in shallow coastal areas. The retention is likely modulated by algal excretions enhancing flocculation of SPM.

The coastal observation system COSYNA aims to describe the physical and biogeochemical state of a regional coastal system. The COSYNA data management (CODM) is the link between observations, model results and data usage. The challenge for CODM is the integration of diverse data sources in terms of parameters, dimensionality and observation methods to gain a comprehensive view of the observations. How this is achieved is described in the paper.