560 
n 
C 
detided SSH at Cuxhaven 
N=39773 | 
:= 0.97 —- 
;msd = 0.07] 
n=. 94 - . 
A 
15 - 
1.0 
0.5 
0.0 - 
-0.5 | 
-1.0 1 
1.5 | ; 
A 
a 
identity line 
- linear fit 
—L 0 1 
detided SSH from GESLAV3.0 
detided SSH at Landsortnorra 
Ür 
0.4 - 
0.2: 
0.0 = 
\ = 43801 
1=0,97 | 
imsd = 0.04 
n= 94 
A 
Fr 
Pr 
ar 
0.2 
} 
_0.4 | 
identity line 
linear fit 
0.6 
_0.50 -0.25 0.00 0.25 0.50 
detided SSH from GESLAvV3.0 
V. Maurer et al.: Evaluation of coupled and uncoupled simulations 
detided SSH at Cuxhaven 
o 
EEE 
N = 39773 
r= 0,94. —- 
rmsd = 0.12 
n= 86 
ED 
0° 
15 - 
1.0 
0.5 - 
0.0 = 
—0.5 + 
1.0 1 
15 
- 101 
- 101 = 
L 
identity line 
„== Iinear fit 
—_ 10% 
Br 
ba 
—L 0 1 
detided SSH from GESLAvV3.0 
— 10 
detided SSH at Landsortnorra 
10“ 
0.6 IN = 43801. _ 
r= 0,97 
rmsd = 0.05 
0.4 1} = 92 ) 
0.2 
0.0 - 
0.2 
ENT 
10 
N 
N | 
101 > 
‚101 => 
—0.4 + 
identity line 
» linear fit 
10° 
Üü 
I 
La 5 
—0.50 —0.25 0.00 0.25 0.50 
detided SSH from GFSLAvV3.0 
— 10° 
Figure 13. Comparison of scatter plots of detided sea surface heights at selected stations in the North Sea and Baltic for NEMO-NBS (left 
panels) vs. ROAM-NBS (right panels). 
4.1 Stratification along the Baltic Thalweg for the 
Maior Baltic Inflow in 2014 
The Baltic Sea is characterized by its strong stratification of 
‚emperature as well as salinity, and its correct representation 
is needed for marine climate applications. To validate the 
stratification, the Baltic thalweg level 4 dataset (Mohrholz, 
2016) is used for temperature and salinity. The interpolated 
gridded CTD (Conductivity, Temperature, Depth) dataset 
contains the longitudes and latitudes of the stations where 
measurements were taken, and these slightly vary with each 
observation cruise. Therefore, the exact coordinates of the 
Dathymetry profiles along the Baltic thalweg in Figs. 14 
and 15 may differ from date to date, but the model data is 
always extracted at the locations given in the observational 
data. An exemplary observational route is shown in Fig. 10a, 
and the distance along the route to the start is plotted on the 
x axis. 
Under typical conditions, the inflow from the North Sea 
into the Baltic Sea through the Danish Straits is relatively 
moderate and exhibits a seasonal cycle. Inflow generally oc- 
curs as dense, saline water entering the Baltic and is strongest 
during late winter and early spring due to wind-driven and 
barotropic forcing (Matthäus and Franck, 1992; Mohrholz, 
Geosci. Model Dev... 19. 543578, 2026 
2018). These inflows gradually ventilate the deep basins of 
the Baltic and maintain the salinity balance (Lehmann et al., 
2022). Under normal circumstances, the inflow is steady 
and predictable, with variations primarily controlled by sea- 
sonal winds, sea-level differences between the North Sea 
and the Baltic Sea, and long-term atmospheric pressure pat- 
terns (Mohrholz, 2018). Significant episodic events in which 
dense, saline water from the North Sea flows through the 
Danish Straits into the Baltic Sea, ventilating its deep basins 
and temporarily raising deep-water salinity and oxygen lev- 
els are called MBI events. 
To evaluate the model simulation’s capability to depict the 
inflow of saline water into the Baltic, thalweg profiles before 
the MBI 2014 (November 2014) and after the MBI event 
(February and March 2015) are displayed for temperature 
(Fig. 14) and salinity (Fig. 15). 
As can be observed in Fig. 14, the temperature thal- 
weg of the coupled ROAM-NBS and ocean stand-alone 
NEMO-NBS simulation only subtly differs. Before the MBI 
event, a temperature bias in the deep basins already ex- 
isted between both model simulations and the observa- 
tional data. The surface temperature obtained with NEMO- 
NBS in November 2014 highly coincides with the observa- 
tional data for 500km «< distance < 1000km, whereas sur- 
https://doi.ore/10.5194/smd-19-543-2026