56 
V. Maurer et al.: Evaluation of coupled and uncoupled simulations 
NBS and ERA5. Further, the coupled model better coincides 
with the displayed maxima, which fits the results obtained in 
the scatter plot at Cuxhaven (Fig. 13). The better represen- 
tation of the SSH maxima in ROAM-NBS can mainly be at- 
tributed to the differences in the treatment of surface bound- 
ary conditions, especially the calculation of the wind stress 
by the surface momentum fluxes (see Sect. 2.3). 
In the Skagerrak, again, the maximum sea level for storm 
events ELON and FELIX in January 2015 is better repre- 
sented by the coupled model, where some of the minimums 
in the time series are better represented by NEMO-NBS. 
At station Travemünde, no high sea level maximum was 
present in January 2015. Higher amplitudes around the max- 
imum sea level (4 January) as well as lower sea level values 
around the sea level minimum (3 January) can be observed 
for ROAM-NBS in comparison to NEMO-NBS. 
7.5 - 
B 
? 5.0 
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Reanalysis 
NEMO NBS 
ROAM NBS 
a 
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a het. ferlibe Dhl 
Figure 17. Annual marine heatwaves metrics computed for the 1o- 
cation Leuchtturm Kiel in the western Baltic Sea from in-situ data at 
0.5 m depth (black), Copernicus Baltic Sea Physics reanalysis data 
(orange), NEMO NBS simulation (blue) and ROAM NBS simu- 
lation (green). Common climatology period is 1993 to 2020. The 
metrics compared here are number of MHW events (a), maximum 
intensity [°C] (b) and total days of MHW conditions (c). The or- 
ange stars indicate the years where reanalysis data is not available, 
which starts in 1993. The black stars indicate years with too large 
data gaps in the in-situ data (1999, 2002, 2015, 2016). 
4.3 Marine heatwaves 
Marine heatwaves (MHWSs) are discrete periods of anoma- 
lously high SSTs. Following the widely used definition by 
Hobday et al. (2016), MHWSs are identified as periods of at 
least five consecutive days during which temperatures exX- 
ceed the 90th percentile of a baseline climatology. To detect 
MHWSs in data and model output, we apply the open-source 
Python package developed by Oliver (2016) to SST data. 
To evaluate model performance in terms of reproduc- 
ing extreme events, we compare three standard MHW met- 
vics — the annual number of events, the maximum intensity, 
and the total number of MHW days per year — across four 
datasets: the two model configurations, in-situ observations, 
and reanalysis data from Copernicus at two locations. The 
locations are chosen based on the availability of long-term 
(> 30 years) observational data. One station is in the west- 
ern Baltic Sea (station Leuchtturm Kiel, 10.27° E, 54.4° N) 
and one in the German Bight (station UFS Deutsche Bucht, 
7.45°E, 54.17° N); see also Fig. 8a for their locations. All 
MHW metrics are computed relative to each dataset’s own 
climatology, using the common baseline period from 1993 
:o 2020. Figure A10 in the Appendix compares the sea- 
sonal climatology and corresponding 90th percentile thresh- 
old across datasets for the station Leuchtturm Kiel. While 
the model shows a small cold bias in this region, the MHW 
detection is not affected by this, as it is performed relative 
to each dataset’s individual climatology. Figure 17 presents 
a comparative analysis of annual MHW metrics at Leucht- 
turm Kiel derived from in-situ observations (black), reanaly- 
sis data (orange), and the two NEMO model configurations: 
NEMO-NBS (blue) and ROAM-NBS (green), spanning the 
period 1989-2020. Figure 17a shows the annual number of 
MHW events, Fig. 17b illustrates the maximum intensity of 
MHWSs (in °C) in each year, and Fig. 17c displays the total 
number of MHW days per year. The same MHW evaluation 
is presented in Fig. A9 for the location UFS Deutsche Bucht. 
Overall, all model configurations capture the inter-annual 
variability in MHW characteristics reasonably well at both 
locations. The NEMO-NBS (blue) generally aligns a lit- 
tle more closely with the observational data in terms of 
event frequency, maximum intensity, and duration, partic- 
ularly in recent years. At Leuchtturm Kiel, the NEMO- 
NBS simulation has a slightly higher Pearson correlation 
coefficient r with the observed events (NEMO-NBS: 0.85, 
ROAM-NBS: 0.84), intensity (NEMO-NBS: 0.57, ROAM- 
NBS: 0.30, ie. not significant) and MHW days (NEMO- 
NBS: 0.97, ROAM-NBS: 0.92). However, discrepancies are 
observed in certain years where model simulations either 
overestimate or underestimate the magnitude and extent of 
MHWSs. For example, at Leuchtturm Kiel, in 2014 and 2018, 
both NEMO-NBS and ROAM-NBS tend to overestimate 
MHW metrics relative to observations, particularly in terms 
of total days and maximum intensity. 
Despite some variability, the model simulations demon- 
strate skill in reproducing the temporal patterns and intensi- 
ties of MHWSs observed in the region, supporting their ap- 
plication for understanding past and projecting future marine 
heatwave conditions. 
Geosci. Model Dev... 19. 543578, 2026 
https:/doi.org/10.5194/smd-19-543-2026