T. Spangehl et al.: Intercomparing the quality of recent reanalyses for offshore wind farm planning 
119 
wind directions in COSMO-REAG, which is consistent with 
the measurements (Fig. 3e). 
Similarly, the wind roses of CERRA, ERA5 and 
HoKliSim-De are in good agreement with observations. The 
underestimation of the wind directions at south-westerly sec- 
tors (WSW, SW, SSW) and overestimation at the sectors W 
:o NNW is somewhat more pronounced in CERRA (Fig. 3b) 
than in COSMO-REA6. However, CERRA shows the ab- 
solute maximum at sector SW which is consistent with ob- 
servations. Moreover, CERRA resembles but underestimates 
the observed secondary maximum at sector E. ERA5S shows 
a clear underestimation of the relative frequency at sector 
5SW. On the other hand, populations at sectors W to NNW 
are slightly overestimated when compared to measurements. 
The relative maximum at sector E is only weakly pronounced 
in ERAS (Fig. 3c). HoKliSim-De shows a slight underesti- 
nation at sectors SSW to WSW, which is most pronounced at 
sector SSW (Fig. 3d). By contrast, populations at sectors W 
(O0 NNW are noticeably overestimated by HoKliSim-De. The 
secondary maximum at sector E is captured by HoKliSim- 
De but less pronounced than in the FINO1 observations 
(Fig. 3e). 
Further quality assessment is provided by analysis of the 
different seasons (Appendix A). One outstanding feature is 
the systematic underestimation of south-westerly wind di- 
rections by the model based products. A systematic under- 
estimation of south-westerly wind directions is also reported 
by Hahmann et al. (2020) for NEWA simulations with WRF. 
A more detailed interpretation of results is beyond the scope 
of the present study. 
tober, CHRISTIAN continued as winter storm with hurri- 
cane strength and moved towards southern Sweden and Fin- 
land. The extreme wind speeds at noon on 28 October in 
the North Sea are also reflected in the various reanalyses in 
Fig. 4. It shows a comparison of hourly wind speed at 100m 
at FINO1 between COSMO-REA6, CERRA and CERRA- 
EDA, ERA5, HoKliSim-De, NEWA and the observations. 
The time series of 7d in Fig. 4a emphasizes that except 
NEWA all products are very well able to represent ampli- 
tude and phase of the storm passage. NEWA significantly un- 
derestimates the maximum wind speeds and also reaches the 
peak too early. Figure 4b shows 28 October in more detail. 
Here, the 10 min observations show that there is a short-term 
wind decrease to 30ms7! between the peaks at 11:00 and 
13:00 UTC. This pattern cannot be reflected by the reanal- 
yses because of the only hourly temporal resolution of the 
available data. The maximum wind intensity is best repro- 
duced by the regional products COSMO-REA6 and CERRA, 
where COSMO-REAG6 even slightly overestimates the maxi- 
mum wind speeds. ERA5 and HoKliSim-De, however, show 
a slight underestimation. Figure 4b also points out a 1 h tem- 
poral shift between the deterministic and ensemble-based 
CERRA product, that has to be investigated further. 
3.2 Comparison against satellite-based products 
Biases of monthly mean near-surface wind speed are anal- 
ysed using a selection of grid points embedded in a geograph- 
ical area covering the German EEZ of the North Sea (3.0 to 
8.5° E, 53.5 to 56 degrees North). 10m wind speed is used 
from models. Two different satellite-based data products are 
used as observational reference. The approach enables an as- 
sessment of the near-surface wind field. 
The first product (WIND_GLO_PHY_L4_MY_012_006, 
hereafter referred to as Scatterometer and Model (e5)) incor- 
porates scatterometer observations used to correct for persis- 
tent biases in hourly ERA5 model fields. The second prod- 
uct (HOAPS version 4.0 + extension, hereafter referred to 
as HOAPS, CMSAF) is based on passive microwave sensor 
measurements. Due to coarser spatial resolution and missing 
data near the coast the HOAPS dataset does not cover the 
complete study area chosen for this analysis. For the covered 
area HOAPS shows a slightly lower 10 m wind speed average 
when compared to the Scatterometer and Model (e5) refer- 
ence dataset from CMEMS (—0.18 ms”! for 2008 to 2017). 
Biases are calculated and discussed separately for the ten 
year period 2008 to 2017 and for the year 2018. The analysis 
for 2018 incorporates in addition results for COSMO-R6G2. 
The year 2018 is characterized by a comparably low value 
of the annual mean wind speed at FINO1 as indicated by 
reanalyses (cf. Sect. 3.1). 
3.1.3 Windstorm CHRISTIAN 
The correct representation of extreme wind speeds in the re- 
analysis systems is shown for storm CHRISTIAN as an ex- 
ample: CHRISTIAN developed over north-western and cen- 
tral Europe in late October 2013 and, with a travelled dis- 
:ance of 1200km in 12h, was classified as a fast-moving 
storm (Deutscher Wetterdienst, 2013). Across Europe, there 
were at least 15 deaths, severe destruction and traffic chaos. 
Affected areas were around the English Channel, in the 
Netherlands, north-western Germany, parts of Denmark and 
southern Sweden (CEDIM, 2013). On 26 October, CHRIS- 
TITAN developed as a secondary cyclone, of the low-pressure 
system BURKHARD over the western Atlantic (Deutscher 
Wetterdienst, 2013). On 27 October, the first gusts with wind 
speeds of up to 133 kmh”! were recorded along the Bre- 
ton coast. On 28 October, CHRISTIAN continued to track 
a0rth-eastward and crossed the south of Great Britain with 
a core pressure of 977 hPa. With a further decrease in pres- 
sure to 968 hPa, CHRISTIAN then moved towards the north- 
west coast of Denmark, triggering the highest wind speeds 
in the North Sea between 13:00 and 14:00 UTC (Deutscher 
Wetterdienst, 2013). Peak wind speeds in northern Germany 
and Denmark exceeded 190 km/h. In the course of 29 Oc- 
attos://doi.org/10.5194/asr-20-109-- u2 
Adv. Sei. Res., 20, 109-128. 2023