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steep slopes, like the North West Shelf. A high resolution
in the upper layers (< 0.18 m in the top layer and < 1.0m
within the upper 16 layers) leads to a good representation
of the ocean’s interface to the atmosphere. The physical pa-
rameterizations and their settings were also chosen as in Ho-
Hagemann et al. (2020). In the turbulence parameterization,
he Generic Length Scale closure is chosen for vertical dif-
fusion, and a geopotential Laplacian operator is used for the
lateral diffusion of the tracers. The iso-level bilaplacian op-
erator is applied within the momentum equations. The three-
dimensional eddy-diffusivity is set to 0.01 m” s7! in the At-
lantic and deeper layers, 0.01 m* s7! in the North Sea, and
0.3 m? s7! within the Baltic. A constant eddy-viscosity of
2.8 x 10° m? s7! is applied throughout the simulations.
A number of changes were made to the original GCOAST
version: In the current work, the updated NEMOv4.2.0
(Madec et al., 2022) with a new sea ice model SI3 (Vancop-
penolle et al., 2023) instead of NEMOv3.6 was used. Be-
sides the model version, an updated bathymetry from the
European Marine Observation and Data Network (EMOD-
net) framework (EMODnet Bathymetry Consortium, 2020),
which comes with a finer resolution, especially relevant for
the coastal representation, has substituted the General Bathy-
metric Chart of the Oceans (GEBCO)-based bathymetry.
Further, manual fine-tuning of the German coasts and Dan-
ish straits and a Laplacian smoothing were applied to the
EMODnet data. In Fig. 1, the depths below 200m are set
cO dark blue to accentuate the European North West Shelf
area. Another modification to the original GCOAST setup
was made in the radiation scheme: a three-band RGB radi-
ation scheme instead of a two-band scheme was used. This
scheme allows for a differentiated treatment of radiation in
the North and Baltic Seas, enabling a better representation
of highly stratified zones. The spatial variability in radia-
tion is represented through a two-dimensional climatologi-
cal field, which captures the mean chlorophyll concentration.
This field serves as a prescribed parameter for the RGB radia-
ion scheme. Since neither ROAM-NBS nor NEMO-NBS in-
cludes a biogeochemical module, the chlorophyll field is de-
rived from literature and observational datasets: Schernewski
et al. (2006) for the Baltic Sea, OSPAR Comission (2017)
for the North Sea, and NASA Earth Observations (2024) for
che Atlantic Ocean. Due to this change, a different radia-
tive penetration of the sea surfaces of the shallower Baltic
Sea and the deeper North Sea could be achieved. The state-
of-the-art Thermodynamic Equation of Seawater (TEOS-10,
https://www.teos-10.org, last access: 26 June 2025) is ap-
plied within NEMO-NBS for the calculation of state vari-
ables.
The river runoff dataset was provided by the German Bun-
desanstalt für Gewässerkunde and combines observational
data in German national waters with model results of the Wa-
terGAP hydrological model (Müller Schmied et al., 2021).
In the NEMO stand-alone setup, atmospheric forcing
fields of the ERA5 reanalysis (Hersbach et al., 2020) in an
hourly temporal resolution are used. These comprise wind
velocities at 10 m height, air temperature and dew point tem-
perature at 2m height, mean sea level pressure, downward
solar and thermal radiations. The surface turbulence and
momentum fluxes are estimated using the ECMWF (2018)
bulk formulation as implemented in the Aereobulk pack-
age (Brodeau et al., 2017). An additional influence is set by
adding atmospheric pressure as an inverse barometer sea Sur-
tace height to the ocean momentum equation.
The main tidal constituents M2, N2, 2N2, $2, K2, K1, O1,
QI1, P1, and M4 for both NEMO-NBS as well as the coupled
ROAM-NBS are provided at the lateral boundaries using the
FES2014 dataset (Lyard et al., 2021).
Within NEMO-NBS and ROAM-NBS, only the ice ther-
modynamics of the SI3 sea ice model is applied, using five
ice categories and two ice layers.
This setup represents one of the first implementations of
NEMOv4.2.0 with SI3 in a fully coupled regional system for
the European shelf, North and Baltic Sea, with direct appli-
cability to coastal hazard and climate risk assessments.
2.3 Coupling via OASIS3-MCT
ICON and NEMO are coupled via the OASIS3-MCT_5.0
coupler (Craig et al., 2017; Valcke et al., 2021). The inter-
faces within the ICON code are based on the implementa-
tion described by Ho-Hagemann et al. (2024). On the NEMO
side, the OASIS3-MCT interfaces are used as provided with
NEMOv4.2.0. In our setup, we are using exclusively the ap-
proach of the flux coupling (Ho-Hagemann et al., 2024),
which has the advantage over the bulk coupling that both
the atmosphere and the ocean model see the same turbulent
fluxes. Additionally, as ICON incorporates a tile approach,
the flux coupling ensures the best possible local conservation
of energy on non-common grids without using an exchange
grid as, for example, Karsten et al. (2024); when variables are
sent from the atmosphere at lower horizontal resolution to the
ocean via OASIS3-MCT, tiled quantities are used. This ap-
proach is very similar to the one used in ICON-XPP (Müller
et al., 2025b). These tiled quantities are representative for the
ocean and sea ice fractions, respectively, in each atmospheric
model grid cell, and are used by the ocean for the compu-
tations for open ocean and sea ice. The respective quanti-
ties are solar shortwave radiation, momentum flux, and the
so-called non-solar radiation, which is the sum of sensible
heat flux, latent heat flux, and long-wave radiation. As the
ice fraction is sent from the ocean model to the atmospheric
one via OASIS3-MCT, the ice fractions of both models are
consistent. In the default NWP and ICON-CLM setup, the
sea ice scheme calculates the heat transfer within the sea
ice, dependent on the current ice depth and a standard bot-
tom temperature. It cannot generate new sea ice, but the ice
thickness can decrease and ice albedo and surface tempera-
ture are determined depending on the heat transfer as well
as on snow Ilving on the ice. To make the thermal part more
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