Station Helgoland Roads in the south-eastern North Sea (German Bight) hosts one of the richest longterm time series of marine observations. Hydrodynamic transport simulations can help understand variability in the local data brought about by intermittent changes of water masses. The objective of our study is to estimate to which extent the outcome of such transport simulations depends on the choice of a specific hydrodynamic model. Our basic experiment consists of 3,377 Lagrangian simulations in time-reversed mode initialized every 7 h within the period Feb 2002-Oct 2004. Fifty-day backward simulations were performed based on hourly current fields from four different hydrodynamic models that are all well established but differ with regard to spatial resolution, dimensionality (2D or 3D), the origin of atmospheric forcing data, treatment of boundary conditions, presence or absence of baroclinic terms, and the numerical scheme. The particle-tracking algorithm is 2D; fields from 3D models were averaged vertically. Drift simulations were evaluated quantitatively in terms of the fraction of released particles that crossed each cell of a network of receptor regions centred at the island of Helgoland. We found substantial systematic differences between drift simulations based on each of the four hydrodynamic models. Sensitivity studies with regard to spatial resolution and the effects of baroclinic processes suggest that differences in model output cannot unambiguously be assigned to certain model properties or restrictions. Therefore, multi-model simulations are needed for a proper identification of uncertainties in long-term Lagrangian drift simulations.

Abstract. Marine spatial planning requires reliable data for, e.g., the design of coastal structures, research, or sea level rise adaptation. This task is particularly ambiguous in the German Bight (North Sea, Europe) because a compromise must be found between economic interests and biodiversity since the environmental status is monitored closely by the European Union. For this reason, we have set up an open-access, integrated marine data collection for the period from 1996 to 2015. It provides bathymetry, surface sediments, tidal dynamics, salinity, and waves for the German Bight and is of interest to stakeholders in science, government, and the economy. This part of a two-part publication presents data from numerical hindcast simulations for sea surface elevation, depth-averaged current velocity, bottom shear stress, depth-averaged salinity, wave parameters, and wave spectra. As an improvement to existing data collections, our data represent the variability in the bathymetry by using annually updated model topographies. Moreover, we provide data at a high temporal and spatial resolution (Hagen et al., 2020b); i.e., numerical model results are gridded to 1000 m at 20 min intervals (https://doi.org/10.48437/02.2020.K2.7000.0004). Tidal characteristic values (Hagen et al., 2020a), such as tidal range or ebb current velocity, are computed based on numerical modeling results (https://doi.org/10.48437/02.2020.K2.7000.0003). Therefore, this integrated marine data collection supports the work of coastal stakeholders and scientists, which ranges from developing detailed coastal models to handling complex natural-habitat problems or designing coastal structures.

Abstract. The German Bight located within the central North Sea is a hydro- and morphodynamically highly complex system of estuaries, barrier islands and part of the world’s largest coherent tidal flats, the Wadden Sea. To identify and understand challenges faced by coastal stakeholders, such as harbor operators or governmental agencies, to maintain waterways and employ numerical models for further analyses, it is imperative to have a consistent data base for both bathymetry and surface sedimentology. Current commercial and public data products are insufficient in spatial and temporal 15 resolution and coverage for recent analyses methods. Thus, this first part of a two-part publication series of the German joint project EasyGSH-DB describes annual bathymetric digital terrain models in a 10 m gridded resolution for the German North Sea coast and German Bight from 1996 to 2016 (Sievers et al., 2020a, https://doi.org/10.48437/02.2020.K2.7000.0001), as well as surface sedimentological models of discretized cumulative grain size distribution functions for 1996, 2006 and 2016 on 100 m grids (Sievers et al., 2020b, https://doi.org/10.48437/02.2020.K2.7000.0005). Furthermore, basic morphodynamic and sedimentological 20 processing analyses, such as the estimation of e.g. bathymetric stability or surface maps of sedimentological parameters, are provided (Sievers et al., 2020a, 2020b, see respective download links).

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The scientific assessment of past and future mean sea level (MSL) trends requires reliable predictions of natural cyclic behavior on short and long time scales, with the current rate of sea-level rise (SLR) being estimated at 2 mm/year in the North Sea (Dangendorf et al., 2015). On a global scale, rates around 1.5 mm/ year between 1900 and 2012 are detected (Oppenheimer et al., 2019) as well as recent accelerations of up to 3 mm/year (Dangendorf et al., 2019). Typical cycles concerning sea level are tides, which are a result of the gravitational potential of sun and moon, centrifugal force of the earth and meteorological forcing. Tides are distinguished by their frequency, which is predominantly diurnal or semidiurnal, even though monthly, interannual, annual, and perennial frequencies exist as well. The nodal tide (Bradley, 1728) is a harmonic signal with a period of 18.61 years, caused by the precession of the lunar ascending node (Pugh, 1987). It is the most important low frequency tidal constituent apart from the lunar perigee and has shown to have an amplitude of up to 30 cm (Peng et al., 2019). In order to consider the nodal tide in MSL analysis, the theoretical equilibrium tide concept is applied (Godin, 1986; Proudman, 1960; Woodworth, 2012). Nonresolved low frequency cyclic behavior of water levels may lead to an erroneous estimation of SLR. The influence