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: 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 for a heavily used coastal area, and Svalbard as an example of an arctic coast that is under strong pressure due to global change. The automated observing and modelling system COSYNA is designed to monitor real time conditions, provide short-term forecasts and data products, and to assess the impact of anthropogenically induced change. Observations are carried out 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 publically available free of charge and in real time. They are used by multiple interest groups in science, agencies, politics, industry, and the public.

Description: The term “SMART Monitoring” is often used in digital projects to survey and analyze data flows in near- or realtime. The term is also adopted in the project Digital Earth (DE) which was jointly launched in 2018 by the eight Helmholtz centers of the research field Earth and Environment (E&E) within the framework of the German Ministry of Education and Research (BMBF). Within DE, the “SMART monitoring” sub-project aims at developing workflows and processes to make scientific parameters and the related datasets SMART, which means specific, measurable, accepted, relevant, and trackable (SMART). “SMART Monitoring” in DE comprises a combination of hard- and software tools to enhance the traditional sequential monitoring approach - where data are step-by-step analyzed and processed from the sensor towards a repository - into an integrated analysis approach where information on the measured value together with the status of each sensor and possible auxiliary relevant sensor data in a sensor network are available and used in real-time to enhance the sensor output concerning data accuracy, precision, and data availability. Thus, SMART Monitoring could be defined as a computer-enhanced monitoring network with automatic data flow control from individual sensors in a sensor network to databases enhanced by automated (machine learning) and near real-time interactive data analyses/exploration using the full potential of all available sensors within the network. Besides, “SMART monitoring” aims to help for a better adjustment of sensor settings and monitoring strategies in time and space in iterative feedback. This poster presentation will show general concepts, workflows, and possible visualization tools based on examples that support the SMART Monitoring idea.

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.