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Full text: Evaluation of coupled and uncoupled ocean\u2013ice\u2013atmosphere simulations using icon-2024.07 and NEMOv4.2.0 for the EURO-CORDEX domain

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V. Maurer et al.: Evaluation of coupled and uncoupled simulations 
consistent with the NEMO/SI3, which has a more detailed 
treatment of thermodynamical processes within sea ice, the 
sea ice albedo, thickness and surface temperature are trans- 
ferred from the ocean to the atmosphere in our setup. The 
ocean albedo over water is not sent, as this option is not avail- 
able in the default coupling setup of NEMOv4.2.0. Only the 
one over ice is available for the coupling. Over the ocean, 
ICON uses a formulation by Taylor et al. (1996) for the di- 
rect albedo and the value of 0.06 for diffuse albedo as in 
ECMWF’s IFS model. Additionally, an albedo increase by 
whitecap cover after Seferian et al. (2018) is considered. 
The complete list of variables exchanged during the cou- 
pling in ROAM-NBS is given in Table 1. For selected vari- 
ables, a global conservation is applied, which means that 
che area average is compared before and after horizontal in- 
terpolation. By selecting “GLBPOS” in the OASIS3-MCT 
settings, the difference between the area average on the tar- 
get minus the source grid is distributed proportionally to the 
value of the original field. 
Because only the respective portions of fluxes for the 
ocean and sea ice tiles are used, flux contributions from land 
points are completely excluded when fluxes are sent from the 
atmosphere to the ocean, which also ensures a consistent eXx- 
change of energy and momentum along the coastlines. As 
suggested by Mechoso et al. (2021) for models that incorpo- 
rate the tile approach, the ocean fraction of the atmospheric 
model is adapted to that of the ocean model, which is ob- 
:ained by interpolating the binary land-sea mask of the ocean 
model to the atmospheric grid. The land and lake fractions of 
‘he atmospheric model are adapted accordingly. For a correct 
treatment of coastal points, great care was put on identical 
interpolation methods for the NEMO land-sea mask and the 
NEMO fields to the ICON grid during coupling, as well as on 
the consistency of the common land-sea mask and the masks 
used by OASIS3-MCT. Thus, the flux coupling as included in 
ROAM-NBS is a good compromise between simplicity and 
correctness. 
especially in coupled mode. To avoid a so-called “cold start”, 
a spin-up for the ocean component was carried out with 
NEMO-NBS for the years 1974-1978, starting with an ini- 
tial field for temperature and salinity. This initial field was, 
in turn, a combined product from the ORAS5S reanalysis and 
the Baltic reanalysis product provided by SMHI (personal 
communication) based on Hordoir et al. (2019). The restart 
field for 1 September 1978 from the spin-up simulation with 
NEMO-NBS was then used to start ROAM-NBS. 
For a better comparison of NEMO-NBS and the ocean part 
of ROAM-NBS, it was decided to use the same observation- 
based dataset for the runoff for both experiments. ICON- 
CLM as well as the atmospheric part of ROAM-NBS were 
started from the ERA5-driven ICON-CLM-UDAG simula- 
don, which had been running since 1940. 
For the atmospheric part, ERAS reanalyses were used as 
lateral boundary conditions, as prescribed by the CORDEX- 
CMIP6 experiment protocol (CORDEX, 2025). They are 
available at a 3-hourly resolution and are also used to pre- 
scribe SST and sea ice in the uncoupled ICON-CLM simula- 
tion. For ROAM-NBS, ERA5 SST and sea ice fields are also 
used in ocean regions outside of the NEMO-NBS domain. As 
lateral boundary conditions for the ocean, the temperature, 
salinity, zonal and meridional ocean velocities, and sea sur- 
face height (SSH) fields from the ORASS5 global reanalysis 
dataset (Zuo et al., 2019) are used. The prescribed fields were 
used at a monthly resolution, as daily data were not available 
for the whole simulation period. To ensure that the spatial 
mean of the modeled SSH fits the observed SSH, the bound- 
ary conditions for the SSH from ORAS5 were bias corrected 
with respect to the SSH at Helgoland from the GESLAv3.0 
observational data (Haigh et al., 2023). This bias was calcu- 
lated on the basis of a 5-year test simulation with uncorrected 
boundary conditions. 
The evaluation is generally conducted for the years 1979- 
2020, which is the minimum period required for CORDEX. 
However, especially for the ocean part, many reference data 
are available for shorter time periods only, so that the eval- 
uation period had to be adapted in these cases: SST and 
sea ice data (CMEMS, 2025a) are available from Septem- 
ber 1981 and surface salinity from 1993 (CMEMS, 2023). 
Station data (CMEMS, 2024a) are very sparse before 1993. 
Copernicus reanalyses used for the evaluation of marine heat 
waves (CMEMS, 2024b, 2025b) start in 1989. For the at- 
mospheric part, satellite data used for the evaluation of sur- 
face radiation (CERES; NASA/LARC/SD/ASDC, 2019) are 
available from 2001 only. Therefore, the evaluated time peri- 
ods had to be adapted in these cases; an overview is given in 
Table 2. For evaluations in which statistics were calculated 
from hourly data, shorter time periods were used, partly due 
to limited data availability as well, partly to reduce the com- 
putational costs (see Sects. 3.2.3 and 3.3.4). 
2.4 Overview of experiments and availability of 
reference data 
The evaluation simulation was run for the coupled 
model (ROAM-NBS) and for both the atmospheric and ocean 
components individually (ICON-CLM and NEMO-NBS, re- 
spectively); Le., we are overall evaluating and comparing 
three simulations. In Sect. 3.2.1, a basic comparison to the 
evaluation simulation from the UDAG project (called ICON- 
CLM-UDAG) is additionally shown. According to CORDEX 
specifications (CORDEX, 2025), “the evaluation experiment 
must cover at least the 1979-2020 period”. Our experiments 
were started in September 1978 because of the stable thermal 
mixed layer in the ocean. Starting in January would mean 
starting in the middle of the winter season when thermal 
conditions are unstable and the sea ice has already evolved, 
which has proven disadvantageous for model initialization, 
Geosci. Model Dev... 19. 543578, 2026 
https://doi.org/10.5194/sgmd-19-543-2026
	        
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