V. Maurer et al.: Evaluation of coupled and uncoupled simulations 
4) 
Table 1. Variables exchanged between the atmosphere and the ocean via OASIS3-MCT; for variables denoted by !, global conservation is 
applied by OASIS3-MCT after horizontal interpolation; NEMO variables denoted by 2 are aggregated over all ice categories before sent to 
che atmosphere; NEMO variables denoted by 3 are rotated from the geographical to the local grid and staggered onto the U, V grid within 
NEMO; “ocean” or “ice” are given in parentheses for ICON variables to indicate that only the part of the variable on the respective tile is 
used. Variables that are combined into other quantities directly in NEMO’s coupling interface are written in bold font. 
Variable NEMO variable 
Ocean — atmosphere 
SST ts (as potential temperature) t_seasfc; t_s; t_s_t(ocean) 
sea ice fraction fr_i fr_seaice 
sea ice albedo alb_ice? albdif_t 
sea ice thickness hi? h_ice 
sea ice (surface) temperature tn_ice? t_ice 
Atmosphere — ocean 
solar radiation!, ocean tile qgsr 
solar radiation, ice tile qsr_ice 
non-solar radiation!, ocean tile qns 
non-solar radiation, ice tile qns_ice 
4-momentum flux, ocean tile utau? 
4-momentum flux, ice tile p_taui? 
v-momentum flux, ocean tile vtau? 
/-momentum flux, ice tile p_tauj? 
precipitation!, liquid part zemp = evap — (rain + snow) 
precipitation!, solid part zemp = evap — (rain + snow) 
evapotranspiration zemp = evap — (rain + snow) 
sublimation evap_ice 
mean sea-level pressure apr; ssh_ib = —(apr — rpref) /(p * g) 
swflxsfc_t(ocean) 
swflxsfe_t(ice) 
I\wfixsfce_t(ocean) + Ihfl_s_t(ocean) + shfl_s_t(ocean) 
Iwfixsfe_t(ice) + Ihfl_s_t(ice) + shfl_s_t(ice) 
umfl_s_t(ocean) 
umfl_s_t(ice) 
vmfl_s_t(ocean) 
vmfl_s_t(ice) 
rain_con_rate + rain_gsp_rate 
5NOW_CON_rate + snow_gsp_rate 
ahfl_s 
ghfl_s_t(ice) 
pres_msl 
3 Evaluation of the mean climate 
on the product-specific Copernicus website. Figure 2a shows 
the difference between the simulated seasonal mean SST of 
ROAM-NBS and the observations. During winter (DJF) and 
spring (MAM), the area in the Northern Baltic is covered by 
sea ice with varying extent over time. In the Copernicus anal- 
yses, the SST is artificially set to —1.8 °C over the regions 
covered by sea ice. The points where these artificial SST val- 
ues are found are masked out for the calculation of the mean 
differences. 
ROAM-NBS shows a cold bias of locally up to 2 K in the 
shallower regions of the European North West Shelf and in 
the Biscaya region during the colder seasons (SON, DJF, 
MAM). In the Baltic, the bias is around zero during these 
seasons. In summer, a positive bias can be observed in most 
parts of the NBS domain apart from the Baltic, where the 
bias becomes negative (up to —1 K in some years in the spa- 
tial average, Fig. 3d). A persistent warm bias is found near 
the northern Atlantic boundary, east of Iceland. This temper- 
ature bias could originate from the northward heat transport 
by the Gulf Stream at the surface and a too weak vertical 
diffusion/downward transport of heat at the model’s bound- 
ary. The border between the positive and negative differences 
in all seasons except summer seems to envelope the Euro- 
pean North West Shelf with a stronger bathymetry gradient. 
To assess the realism of the coupled ROAM-NBS system, we 
evaluate its representation of the present-day climate over the 
North and Baltic Seas in comparison with the atmosphere- 
only (ICON-CLM) and ocean-only (NEMO-NBS) simula- 
tions. The seasonal means are calculated for the main ocean- 
atmosphere surface variables to evaluate the performance of 
ROAM-NBS and its individual components with respect to 
climate timescales. Mean temperature and salinity profiles 
are validated in the Baltic to assess the ocean components’ 
ability to model highly stratified regions. Statistical values 
for the sea surface height are presented for stations through- 
out the ocean domain. 
3.1 Sea surface temperature 
The most crucial variable at the interface of the atmosphere 
and the ocean is the SST, as it serves as the first indicator of 
the model’s performance and proper coupling. Here, the sim- 
ılated SST is compared to satellite observations from Coper- 
nicus. The Copernicus observations used are available from 
September 1981 to December 2024. Detailed information on 
the quality of the observational data is provided in the quality 
information document of the dataset, which can also be found 
https:/doi.o0rg/10.5194/smd-19-543-20246 
Geosci. Model Dev.., 19. 543-578, 2026