1 
T. Spangehl et al.: Intercomparing the quality of recent reanalyses for offshore wind farm planning 
data has to be evaluated. COSMO model Version 5.04d was 
operationally used by DWD from 12 December 2016 to 
23 March 2017 and is the latest model version that was oper- 
ationally used with nudging. Therefore, COSMO-R6G2 uses 
COSMO model version 5.04d4. Here we present results from 
a first simulation stream for 2018. 
based Global Navigation Satellite Systems (GNSS), radio 
occultation GNSS, scatterometer winds, atmospheric motion 
vectors and surface observations from local sources are used 
in the analyses. A new way of creating and updating the 
background error covariance matrix is used in order to fol- 
low the current weather regime and to allow for possible 
evolutions in the weather over the reanalysis period (El-Said 
et al., 2022). The surface assimilation uses an optimal in- 
terpolation assimilation scheme for the surface observations 
(e.g. Taillefer, 2002; Seity et al., 2011). The observations in- 
cluded are relative humidity and temperature at 2m height 
obtained from SYNOP stations as well as the snow water 
equivalent. Also, for the surface assimilation additional ob- 
servations from local sources are included. In the present 
study the 10 and 100 m wind speed and direction of CERRA 
are used (Schimanke et al., 2021b, a). The following data is 
used from the deterministic system (CERRA-DET). Monthly 
averages of the 10m wind speed are calculated from the 3- 
hourly analyses (hereafter referred to as CERRA-an). The 
hourly 100m wind speed and direction are obtained from 
forecasts (CERRA-fc) using lead time hours T+1, T+2 
and T +3 (T =analysis time step). Direct comparison of 
CERRA-an and CERRA-fc reveals only small differences. In 
addition to CERRA-DET, hourly data of 100 m wind speed 
from the ensemble of data assimilations (CERRA-EDA, lead 
time hours T+1,..., T +6 used) is analysed. CERRA-EDA 
is a 10-member ensemble of 3D-Var data assimilations with 
a 6h cycle and 11km horizontal grid spacing. 
2.1.4 ERAS 
ERAS is the fifth generation ECMWF atmospheric reanaly- 
sis and covers the period from 1940 to present. It is based 
on the Integrated Forecasting System (IFS) Cy41r2 which 
was operational in 2016 (Hersbach et al., 2020). The spatial 
horizontal resolution is 0.28° or 31km (spectral truncation 
T639). In the vertical there are 137 levels from the surface 
to the model top located at 0.01 hPa or 80km. 4DVar is used 
for the assimilation of a variety of conventional and satellite 
Jased observational data. ERAS5 includes information about 
uncertainties for all variables at reduced spatial and temporal 
resolutions. Quality-assured monthly updates of ERA5 are 
published within 3 months of real time. Preliminary daily 
updates of the dataset are available to users within 5 d of real 
time. A detailed description and evaluation results are given 
by Hersbach et al. (2020). Access to the data is provided by 
Meteorological Archival and Retrieval System (MARS) and 
Copernicus Climate Data Store (CDS). 
2.1.5 Copernicus European Regional Re-Analysis 
(/CERRA) 
The CERRA system builds on the HARMONIE script Sys- 
:em cycle 40h1.2. Several changes and optimisations in the 
script system have been made, compared to the reference 
version of HARMONIE, to make the model run more ef- 
ficiently in a re-analysis production environment. The AL- 
ADIN synoptic scale physics scheme is used including sev- 
eral updates from later cycles that are backported to fit with 
cy40h1.2. The model runs with a 5.5 km horizontal grid spac- 
ing and with 106 vertical levels. The model domain is some- 
what larger than the Euro-CORDEX domain. It runs with 
a 3h cycle producing 6h forecasts at all analysis times ex- 
cept at 00:00 and 12:00 UTC where 30h forecasts are pro- 
duced. Information about sea surface temperature and sea ice 
are obtained from the Operational Sea Surface Temperature 
and Sea Ice Analysis (OSTIA) database (Donlon et al., 2012; 
Stark et al., 2008). The boundary information is taken from 
(he ERA5 output. Upper air observations are introduced into 
che model through a three-dimensional variational (3D-Var) 
data assimilation scheme (e.g. Gustafsson et al., 2001; Lind- 
skog et al., 2001; Brousseau et al., 2008). Included obser- 
vations are the conventional observations, i.e. observations 
from SYNOP stations, ships, buoys aircrafts and radioson- 
des, together with satellite radiances from the early Mi- 
crowave Sounding Unit (MSU) to the latest Infrared Atmo- 
spheric Sounding Interferometer (IASD. In addition, ground- 
2.2 Simulations without data assimilation: climate 
simulation (COSMO-CLM) and wind atlas (WRF) 
2.2.1 High resolution simulation with 
COSMO-CLM (HokKliSim-De) 
HoKliSim-De (“High resolution COSMO-CLM climate sim- 
ılation with ERA reanalysis forcing for Germany”) is a 
nearly 50-year dataset which downscales the European re- 
analysis datasets ERA40 (Uppala et al., 2005, for the years 
1971-1978) and ERA5 (Hersbach et al., 2020, for 1979- 
2019) on a higher-resolution grid for Germany. The regional 
climate model COSMO-CLM (COSMO model in CLimate 
Mode; Rockel et al., 2008; Steger and Bucchignani, 2020) is 
used for this downscaling in a convection-permitting setup. 
The COSMO-CLM is the climate version of the limited-area 
weather forecast model COSMO (Baldauf et al., 2011; Doms 
et al., 2013) and it is the community model of the German 
regional climate research community jointly further devel- 
oped by the CLM-Community (http://www.clm-community. 
eu, last access: 6 November 2023). It has been proven to be 
suitable for regional climate model simulations at grid scales 
between 1 and 50km in Central Europe in numerous studies 
(e.g. Berg et al., 2013; Kotlarski et al., 2014; Brienen et al., 
2016: Ban et al., 2021). In a recent study by Borgers et al. 
Adv. Sci. Res... 20. 109-128. 202, 
httos://doi.org/10.5194/asr-20-109-2023