ALBERT

Description: A thorough and reliable assessment of changes in sea surface water temperatures (SSWTs) is essential for understanding the effects of global warming on long-term trends in marine ecosystems and their communities. The first long-term temperature measurements were established almost a century ago, especially in coastal areas, and some of them are still in operation. However, while in earlier times these measurements were done by hand every day, current environmental long-term observation stations (ELTOS) are often fully automated and integrated in cabled underwater observatories (UWOs). With this new technology, year-round measurements became feasible even in remote or difficult to access areas, such as coastal areas of the Arctic Ocean in winter, where measurements were almost impossible just a decade ago. In this context, there is a question over what extent the sampling frequency and accuracy influence results in long-term monitoring approaches. In this paper, we address this with a combination of lab experiments on sensor accuracy and precision and a simulated sampling program with different sampling frequencies based on a continuous water temperature dataset from Svalbard, Arctic, from 2012 to 2017. Our laboratory experiments showed that temperature measurements with 12 different temperature sensor types at different price ranges all provided measurements accurate enough to resolve temperature changes over years on a level discussed in the literature when addressing climate change effects in coastal waters. However, the experiments also revealed that some sensors are more suitable for measuring absolute temperature changes over time, while others are more suitable for determining relative temperature changes. Our simulated sampling program in Svalbard coastal waters over 5 years revealed that the selection of a proper sampling frequency is most relevant for discriminating significant long-term temperature changes from random daily, seasonal, or interannual fluctuations. While hourly and daily sampling could deliver reliable, stable, and comparable results concerning temperature increases over time, weekly sampling was less able to reliably detect overall significant trends. With even lower sampling frequencies (monthly sampling), no significant temperature trend over time could be detected. Although the results were obtained for a specific site, they are transferable to other aquatic research questions and non-polar regions.

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.