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: The estimations of the diffusive methane flux from the water phase into the atmosphere in coastal waters is relevant for a better estimate of the atmospheric greenhouse-gas budget. Unfortunately, so far, the numerical determination of the fluxes has a high level of uncertainty in coastal waters. To improve the estimation of coastal methane fluxes, not only a high temporal and spatial sampling resolution of the dissolved methane in the water are required. Besides, also the atmospheric methane concentration and the wind speed and wind direction above the surface is important. In most cases, these atmospheric data are obtained from near-by atmospheric and meteorologic monitoring stations. In this study, we measured wind speed, direction and atmospheric methane local directly on board of three research vessel cruising in the southern North Sea within the MOSES project and compared the effects of local versus remote measurements of these data on the flux data. In addition, using the wind direction and speed, we try to assess the origin of the atmospheric methane measured in the study area. Using these “improved” data sets, we discuss if local measurements of auxiliary data provide better insights in the determining factors of the methane flux, and thus also improve the regional aquatic methane budget.

Description: Nutrient and carbon dynamics within the river-estuary-coastal water systems are key processes to understand the matter fluxes from the terrestrial environment to the ocean. In a large-scale study we analysed those dynamics with the focus of the prevailing low water conditions by following a sampling approach based on the travel time of water. We started with a nearly Lagrangian sampling along the River Elbe (German part; 580 km within 8 days travel time). After a subsequent investigation of the estuary, the plume of the river was followed by raster sampling the German Bight (North Sea) using three ships simultaneously. In the river, intensive growth of phytoplankton was determined connected with high oxygen saturation and pH values as well as under-saturation of CO2, whereas concentrations of dissolved nutrients declined. In the estuary, the Elbe shifted from an autotrophic to a heterotrophic system: Phytoplankton died off upstream of the salinity gradient causing minima in oxygen saturation and pH, supersaturation of CO2, and a release of nutrients. In the coastal region, phytoplankton and nutrient concentrations were low, oxygen close to saturation, and pH in a typical marine range. We detected a positive relationship between pH values and oxygen saturation and a negative one between pCO2 and oxygen saturation. Corresponding to the significant particulate nutrient flux via phytoplankton, flux rates of dissolved nutrients from the river into the estuary were low and determined by depleted concentrations. In contrast, fluxes from the estuary to the coastal waters were higher and the pattern was determined by tidal currents. Overall, the presented observation approach is appropriate to better understand land-ocean fluxes, particularly if it is performed under different hydrological conditions including extremes and seems to be suitable to investigate the impact of such events in freshwater on coastal systems in future. The study was conducted within the frame of the Helmholtz MOSES initiative (Modular Observation Solutions for Earth Systems) targeting processes and impacts of hydrological extremes.